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Sample records for optimal expansion planning

  1. Considering FACTS in Optimal Transmission Expansion Planning

    Directory of Open Access Journals (Sweden)

    K. Soleimani

    2017-10-01

    Full Text Available The expansion of power transmission systems is an important part of the expansion of power systems that requires enormous investment costs. Since the construction of new transmission lines is very expensive, it is necessary to choose the most efficient expansion plan that ensures system security with a minimal number of new lines. In this paper, the role of Flexible AC Transmission System (FACTS devices in the effective operation and expansion planning of transmission systems is examined. Effort was taken to implement a method based on sensitivity analysis to select the optimal number and location of FACTS devices, lines and other elements of the transmission system. Using this method, the transmission expansion plan for a 9 and a 39 bus power system was performed with and without the presence of FACTS with the use of DPL environment in Digsilent software 15.1. Results show that the use of these devices reduces the need for new transmission lines and minimizes the investment cost.

  2. Generation Expansion Planning as Particle Swarm Optimization with Gridified SATyrus

    International Nuclear Information System (INIS)

    Diacovo, R.; Franca, F. M. G.; Lima, P. M. V.

    2007-01-01

    This work introduces our first attempt on using the Grid to solve a real-life problem with the SATyrus platform. In electrical engineering, a challenging task is to find the less expensive ways to expand the energy production capacity, supporting an increasing demand. This is the definition of the generation expansion planning problem (GEP). We decided to investigate the Particle Swarm Optimization (PSO) paradigm for this task, due to its efficiency and arbitrary memory requirements, the last one being a desirable characteristic for any solver running on a Grid environment. The PSO was used in conjunction with the SATyrus platform, which stands for an energy function synthesizer. We hope the results presented here will help to evolve SATyrus into a reliable generic problem solver. (Author)

  3. Optimizing Transmission Network Expansion Planning With The Mean Of Chaotic Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abdelaziz

    2015-08-01

    Full Text Available This paper presents an application of Chaotic differential evolution optimization approach meta-heuristics in solving transmission network expansion planning TNEP using an AC model associated with reactive power planning RPP. The reliabilityredundancy of network analysis optimization problems implicate selection of components with multiple choices and redundancy levels that produce maximum benefits can be subject to the cost weight and volume constraints is presented in this paper. Classical mathematical methods have failed in handling non-convexities and non-smoothness in optimization problems. As an alternative to the classical optimization approaches the meta-heuristics have attracted lot of attention due to their ability to find an almost global optimal solution in reliabilityredundancy optimization problems. Evolutionary algorithms EAs paradigms of evolutionary computation field are stochastic and robust meta-heuristics useful to solve reliabilityredundancy optimization problems. EAs such as genetic algorithm evolutionary programming evolution strategies and differential evolution are being used to find global or near global optimal solution. The Differential Evolution Algorithm DEA population-based algorithm is an optimal algorithm with powerful global searching capability but it is usually in low convergence speed and presents bad searching capability in the later evolution stage. A new Chaotic Differential Evolution algorithm CDE based on the cat map is recommended which combines DE and chaotic searching algorithm. Simulation results and comparisons show that the chaotic differential evolution algorithm using Cat map is competitive and stable in performance with other optimization approaches and other maps.

  4. An optimization framework for the integrated planning of generation and transmission expansion in interconnected power systems

    International Nuclear Information System (INIS)

    Guerra, Omar J.; Tejada, Diego A.; Reklaitis, Gintaras V.

    2016-01-01

    Highlights: • A novel optimization framework for the design and planning of interconnected power systems is proposed. • The framework integrates generation and transmission capacity expansion planning. • Reserve and emission constraints are included. • Business as usual and CO_2 mitigation policy scenarios are evaluated. • Reconfiguration of existing power generation technologies is the most cost-effective option for CO_2 emissions mitigation. - Abstract: Energy, and particularly electricity, has played and will continue to play a very important role in the development of human society. Electricity, which is the most flexible and manageable energy form, is currently used in a variety of activities and applications. For instance, electricity is used for heating, cooling, lighting, and for operating electronic appliances and electric vehicles. Nowadays, given the rapid development and commercialization of technologies and devices that rely on electricity, electricity demand is increasing faster than overall primary energy supply. Consequently, the design and planning of power systems is becoming a progressively more important issue in order to provide affordable, reliable and sustainable energy in timely fashion, not only in developed countries but particularly in developing economies where electricity demand is increasing even faster. Power systems are networks of electrical devices, such as power plants, transformers, and transmission lines, used to produce, transmit, and supply electricity. The design and planning of such systems require the selection of generation technologies, along with the capacity, location, and timing of generation and transmission capacity expansions to meet electricity demand over a long-term horizon. This manuscript presents a comprehensive optimization framework for the design and planning of interconnected power systems, including the integration of generation and transmission capacity expansion planning. The proposed

  5. Generation expansion planning in Pool market: A hybrid modified game theory and particle swarm optimization

    International Nuclear Information System (INIS)

    Moghddas-Tafreshi, S.M.; Shayanfar, H.A.; Saliminia Lahiji, A.; Rabiee, A.; Aghaei, J.

    2011-01-01

    Unlike the traditional policy, Generation Expansion Planning (GEP) problem in competitive framework is complicated. In the new policy, each GENeration COmpany (GENCO) decides to invest in such a way that obtains as much profit as possible. This paper presents a new hybrid algorithm to determine GEP in a Pool market. The proposed algorithm is divided in two programming levels: master and slave. In the master level a modified game theory (MGT) is proposed to evaluate the contrast of GENCOs by the Independent System Operator (ISO). In the slave level, a particle swarm optimization (PSO) method is used to find the best solution of each GENCO for decision-making of investment. The validity of the proposed method is examined in the case study including three GENCOs with multi-types of power plants. The results show that the presented method is both satisfactory and consistent with expectation.

  6. Optimal expansion planning of stand-alone systems with stochastic simulations

    Energy Technology Data Exchange (ETDEWEB)

    Hoese, Alejandro [Instituto de Energia Electrica (IEE), Universidad Nacional de San Juan, (Argentina)

    1997-12-31

    Stand-alone systems in the range of 1 kW - 10 MW are taking relevance in the new (global) liberal concept of energy market. State and private investors are becoming increasingly attention on the use of renewable for these systems, but it must be shown that these non-conventional solutions are competitive with the established conventional ones. The high investment costs and the technical and economic uncertainties coupled with the use of time-dependent energy sources are the mainly inhibiting factors for the decision agents to choose these systems instead of conventional ones. In the paper a new model for optimal expansion planning of hybrid stand-alone generating systems under consideration of uncertainties is presented. This model is at present in {sup d}evelopment state{sup .} Results already obtained in the first steps of this research are promising and some of them are here presented. [Espanol] Los sistemas autocontenidos en el rango de 1 Kw a 10 MW estan tomando importancia en el nuevo (global) concepto liberal del mercado de la energia. Inversionistas privados y del Estado estan poniendo mayor atencion en el uso de energias renovables para estos sistemas, pero debe mostrarse que estas soluciones no-convencionales son competitivas con las convencionales establecidas. Los altos costos de inversion y las incertidumbres tecnicas y economicas aunadamente con el uso de fuentes de energia dependientes del tiempo son los principales factores inhibidores de los factores de decision para escoger estos sistemas en lugar de los convencionales. En este articulo se presenta un nuevo modelo de planeacion de expansion optima de sistemas hibridos autocontenidos de generacion electrica bajo la consideracion de incertidumbres. Este modelo esta actualmente en {sup e}stado de desarrollo{sup .} Los resultados ya obtenidos en las primeras etapas de esta investigacion son prometedores y se presentan algunos de ellos.

  7. Optimal expansion planning of stand-alone systems with stochastic simulations

    Energy Technology Data Exchange (ETDEWEB)

    Hoese, Alejandro [Instituto de Energia Electrica (IEE), Universidad Nacional de San Juan, (Argentina)

    1998-12-31

    Stand-alone systems in the range of 1 kW - 10 MW are taking relevance in the new (global) liberal concept of energy market. State and private investors are becoming increasingly attention on the use of renewable for these systems, but it must be shown that these non-conventional solutions are competitive with the established conventional ones. The high investment costs and the technical and economic uncertainties coupled with the use of time-dependent energy sources are the mainly inhibiting factors for the decision agents to choose these systems instead of conventional ones. In the paper a new model for optimal expansion planning of hybrid stand-alone generating systems under consideration of uncertainties is presented. This model is at present in {sup d}evelopment state{sup .} Results already obtained in the first steps of this research are promising and some of them are here presented. [Espanol] Los sistemas autocontenidos en el rango de 1 Kw a 10 MW estan tomando importancia en el nuevo (global) concepto liberal del mercado de la energia. Inversionistas privados y del Estado estan poniendo mayor atencion en el uso de energias renovables para estos sistemas, pero debe mostrarse que estas soluciones no-convencionales son competitivas con las convencionales establecidas. Los altos costos de inversion y las incertidumbres tecnicas y economicas aunadamente con el uso de fuentes de energia dependientes del tiempo son los principales factores inhibidores de los factores de decision para escoger estos sistemas en lugar de los convencionales. En este articulo se presenta un nuevo modelo de planeacion de expansion optima de sistemas hibridos autocontenidos de generacion electrica bajo la consideracion de incertidumbres. Este modelo esta actualmente en {sup e}stado de desarrollo{sup .} Los resultados ya obtenidos en las primeras etapas de esta investigacion son prometedores y se presentan algunos de ellos.

  8. A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm

    International Nuclear Information System (INIS)

    Ahmadigorji, Masoud; Amjady, Nima

    2016-01-01

    In this paper, a new model for MEPDN (multiyear expansion planning of distribution networks) is proposed. By solving this model, the optimal expansion scheme of primary (i.e. medium voltage) distribution network including the reinforcement pattern of primary feeders as well as location and size of DG (distributed generators) during an ascertained planning period is determined. Furthermore, the time-based feature of proposed model allows it to specify the investments/reinforcements time (i.e. year). Moreover, a minimum load shedding-based analytical approach for optimizing the network's reliability is introduced. The associated objective function of proposed model is minimizing the total investment and operation costs. To solve the formulated MEPDN model as a complex multi-dimensional optimization problem, a new evolutionary algorithm-based solution method called BCSSO (Binary Chaotic Shark Smell Optimization) is presented. The effectiveness of the proposed MEPDN model and solution approach is illustrated by applying them on two widely-used test cases including 12-bus and 33-bus distribution network and comparing the acquired results with the results of other solution methods. - Highlights: • A multiyear expansion planning model for distribution network is presented. • A new evolutionary algorithm-based solution approach is proposed. • A minimum load shedding-based analytical method for EENS minimization is suggested. • The efficacy of the proposed solution approach is broadly investigated.

  9. Multi-objective and multi-criteria optimization for power generation expansion planning with CO2 mitigation in Thailand

    Directory of Open Access Journals (Sweden)

    Kamphol Promjiraprawat

    2013-06-01

    Full Text Available In power generation expansion planning, electric utilities have encountered the major challenge of environmental awareness whilst being concerned with budgetary burdens. The approach for selecting generating technologies should depend on economic and environmental constraint as well as externalities. Thus, the multi-objective optimization becomes a more attractive approach. This paper presents a hybrid framework of multi-objective optimization and multi-criteria decision making to solve power generation expansion planning problems in Thailand. In this paper, CO2 emissions and external cost are modeled as a multi-objective optimization problem. Then the analytic hierarchy process is utilized to determine thecompromised solution. For carbon capture and storage technology, CO2 emissions can be mitigated by 74.7% from the least cost plan and leads to the reduction of the external cost of around 500 billion US dollars over the planning horizon. Results indicate that the proposed approach provides optimum cost-related CO2 mitigation plan as well as external cost.

  10. Cast Off expansion plan by rapid improvement through Optimization tool design, Tool Parameters and using Six Sigma’s ECRS Technique

    Science.gov (United States)

    Gopalakrishnan, T.; Saravanan, R.

    2017-03-01

    Powerful management concepts step-up the quality of the product, time saving in producing the product thereby increase the production rate, improves tools and techniques, work culture, work place and employee motivation and morale. In this paper discussed about the case study of optimizing the tool design, tool parameters to cast off expansion plan according ECRS technique. The proposed designs and optimal tool parameters yielded best results and meet the customer demand without expansion plan. Hence the work yielded huge savings of money (direct and indirect cost), time and improved the motivation and more of employees significantly.

  11. Energy expansion planning by considering electrical and thermal expansion simultaneously

    International Nuclear Information System (INIS)

    Abbasi, Ali Reza; Seifi, Ali Reza

    2014-01-01

    Highlights: • This paper focused on the expansion planning optimization of energy systems. • Employing two form of energy: the expansion of electrical and thermal energies. • The main objective is to minimize the costs. • A new Modified Honey Bee Mating Optimization (MHBMO) algorithm is applied. - Abstract: This study focused on the expansion planning optimization of energy systems employing two forms of energy: the expansion of electrical and thermal energies simultaneously. The main objective of this investigation is confirming network adequacy by adding new equipment to the network, over a given planning horizon. The main objective of the energy expansion planning (EEP) is to minimize the real energy loss, voltage deviation and the total cost of installation equipments. Since the objectives are different and incommensurable, it is difficult to solve the problem by the conventional approaches that may optimize a single objective. So, the meta-heuristic algorithm is applied to this problem. Here, Honey Bee Mating Optimization algorithm (HBMO) as a new evolutionary optimization algorithm is utilized. In order to improve the total ability of HBMO for the global search and exploration, a new modification process is suggested such a way that the algorithm will search the total search space globally. Also, regarding the uncertainties of the new complicated energy systems, in this paper for the first time, the EEP problem is investigated in a stochastic environment by the use of probabilistic load flow technique based on Point Estimate Method (PEM). In order to evaluate the feasibility and effectiveness of the proposed algorithm, two modified test systems are used as case studies

  12. Thai gas expansion plans

    International Nuclear Information System (INIS)

    Hayes, D.

    2001-01-01

    Demand for natural gas in Thailand is increasing significantly as the Electricity Generating Authority of Thailand and the independent private power producers (IPPs) switch from oil to gas to fire their power stations in line with Government policy to reduce oil imports and use more gas from the Gulf of Thailand. The Petroleum Authority of Thailand (PTT) has the sole right to buy and sell natural gas and other petroleum products in Thailand. According to PTT, the surge in demand for natural gas in the first half of 2001 was matched by a fall in demand for refined oil products. The PTT has received Government approval to convert to a limited company ready for listing on the Thai Stock Exchange. This is expected to further increase gas consumption. Details of gas sales to power generation and other industrial sectors by PTT and Unocal, Thailand's largest producer, are given. PTT operations include work to extend its gas pipeline transmission system. A number of new pipeline schemes are planned, including one across southern Thailand to transfer offshore gas from the Joint Development Area gas field owned by Thailand and Malaysia. This has encountered protests over the proposed plant and pipeline route

  13. Scalable and practical multi-objective distribution network expansion planning

    NARCIS (Netherlands)

    Luong, N.H.; Grond, M.O.W.; Poutré, La J.A.; Bosman, P.A.N.

    2015-01-01

    We formulate the distribution network expansion planning (DNEP) problem as a multi-objective optimization (MOO) problem with different objectives that distribution network operators (DNOs) would typically like to consider during decision making processes for expanding their networks. Objectives are

  14. Decennial plan of expansion 1994-2003

    International Nuclear Information System (INIS)

    1993-12-01

    The Decennial Plan of Expansion 1994-2003 of Electric sector reproduces the results of the studies occurred during the planning cycle of 1992/93 from the Coordinator Groups of the Electric System Planning. Based in the market forecasting, economic-financier and time for finishing the the works, the Decennial Plan of Expansion presents the schedule of the main generation and transmission works for the next ten years, the annual spend in generation, transmission and distribution, the costs of expansion and the evaluation of attending conditions in electric system in Brazil. (C.G.C.)

  15. Advanced methodology for generation expansion planning including interconnected systems

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, M; Yokoyama, R; Yasuda, K [Tokyo Metropolitan Univ. (Japan); Sasaki, H [Hiroshima Univ. (Japan); Ogimoto, K [Electric Power Development Co. Ltd., Tokyo (Japan)

    1994-12-31

    This paper reviews advanced methodology for generation expansion planning including interconnected systems developed in Japan, putting focus on flexibility and efficiency in a practical application. First, criteria for evaluating flexibility of generation planning considering uncertainties are introduced. Secondly, the flexible generation mix problem is formulated as a multi-objective optimization with more than two objective functions. The multi-objective optimization problem is then transformed into a single objective problem by using the weighting method, to obtain the Pareto optimal solution, and solved by a dynamics programming technique. Thirdly, a new approach for electric generation expansion planning of interconnected systems is presented, based on the Benders Decomposition technique. That is, large scale generation problem constituted by the general economic load dispatch problem, and several sub problems which are composed of smaller scale isolated system generation expansion plans. Finally, the generation expansion plan solved by an artificial neural network is presented. In conclusion, the advantages and disadvantages of this method from the viewpoint of flexibility and applicability to practical generation expansion planning are presented. (author) 29 refs., 10 figs., 4 tabs.

  16. Electric Grid Expansion Planning with High Levels of Variable Generation

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); You, Shutang [Univ. of Tennessee, Knoxville, TN (United States); Shankar, Mallikarjun [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Liu, Yilu [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-02-01

    Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind power across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance

  17. Generation Expansion Planning Considering Integrating Large-scale Wind Generation

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Ding, Yi; Østergaard, Jacob

    2013-01-01

    necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. A bi-level generation expansion planning approach considering large-scale wind generation was proposed in this paper. The first phase is investment decision, while the second phase is production...... optimization decision. A multi-objective PSO (MOPSO) algorithm was introduced to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of the proposed bi-level planning approach and the MOPSO...

  18. Expansion planning for electrical generating systems

    International Nuclear Information System (INIS)

    1984-01-01

    The guidebook outlines the general principles of electric power system planning in the context of energy and economic planning in general. It describes the complexities of electric system expansion planning that are due to the time dependence of the problem and the interrelation between the main components of the electric system (generation, transmission and distribution). Load forecasting methods are discussed and the principal models currently used for electric system expansion planning presented. Technical and economic information on power plants is given. Constraints imposed on power system planning by plant characteristics (particularly nuclear power plants) are discussed, as well as factors such as transmission system development, environmental considerations, availability of manpower and financial resources that may affect the proposed plan. A bibliography supplements the references that appear in each chapter, and a comprehensive glossary defines terms used in the guidebook

  19. Regulatory Holidays and Optimal Network Expansion

    NARCIS (Netherlands)

    Willems, Bert; Zwart, Gijsbert

    2016-01-01

    We model the optimal regulation of continuous, irreversible, capacity expansion, in a model in which the regulated network firm has private information about its capacity costs, investments need to be financed out of the firm’s cash flows from selling network access and demand is stochastic. If

  20. Gas fuels Taiwan's expansion plans

    International Nuclear Information System (INIS)

    Hayes, David

    2000-01-01

    The volume of liquid natural gas (LNG) imported into Taiwan is expected to double over the next ten years as the use of natural gas for power generation increases significantly. The Chinese Petroleum Corporation (CPC) expects to import 4.5 million tonnes of LNG in 2000 compared with 4 million tonnes in 1999. CPC is building an undersea, offshore pipeline from the Yung An LNG terminal in the south of Taiwan up the western coastline to the north. The pipeline will supply gas to power stations in the north and city gas companies in Taipei. Combined cycle power plant units at Tungshiao power station are converting to gas and a new power plant at Changsheng will burn LNG. More LNG power plants are planned. LNG is imported from Indonesia and Malaysia to supplement Taiwan's dwindling reserves of natural gas. As well as expanding the existing terminal at Yung An, the CPC is considering the need for a second import terminal. This would probably be financed and operated by the private sector

  1. Combination of AC Transmission Expansion Planning and Reactive Power Planning in the restructured power system

    International Nuclear Information System (INIS)

    Hooshmand, Rahmat-Allah; Hemmati, Reza; Parastegari, Moein

    2012-01-01

    Highlights: ► To overcome the disadvantages of DC model in Transmission Expansion Planning, AC model should be used. ► The Transmission Expansion Planning associated with Reactive Power Planning results in fewer new transmission lines. ► Electricity market concepts should be considered in Transmission Expansion Planning problem. ► Reliability aspects should be considered in Transmission Expansion Planning problem. ► Particle Swarm Optimization is a suitable optimization method to solve Transmission Expansion Planning problem. - Abstract: Transmission Expansion Planning (TEP) is an important issue in power system studies. It involves decisions on location and number of new transmission lines. Before deregulation of the power system, the goal of TEP problem was investment cost minimization. But in the restructured power system, nodal prices, congestion management, congestion surplus and so on, have been considered too. In this paper, an AC model of TEP problem (AC-TEP) associated with Reactive Power Planning (RPP) is presented. The goals of the proposed planning problem are to minimize investment cost and maximize social benefit at the same time. In the proposed planning problem, in order to improve the reliability of the system the Expected Energy Not Supplied (EENS) index of the system is limited by a constraint. For this purpose, Monte Carlo simulation method is used to determine the EENS. Particle Swarm Optimization (PSO) method is used to solve the proposed planning problem which is a nonlinear mixed integer optimization problem. Simulation results on Garver and RTS systems verify the effectiveness of the proposed planning problem for reduction of the total investment cost, EENS index and also increasing social welfare of the system.

  2. The reference electricity expansion plan of Guatemala

    International Nuclear Information System (INIS)

    Santizo, Rodolfo

    2002-01-01

    This presentation prepared by the Deputy Minister of Energy and Mines overviews the following issues: description of electric power infrastructure, price markets, expansion plans, power and energy demand projections through 2010, including bussiness opportunities for private investment on geothermal and hidro electric power production and distribution market. This presentation is intended for private investors who could be interested in bussiness opportunities of energy generation market in Guatemala

  3. A computational model for determining the minimal cost expansion alternatives in transmission systems planning

    International Nuclear Information System (INIS)

    Pinto, L.M.V.G.; Pereira, M.V.F.; Nunes, A.

    1989-01-01

    A computational model for determining an economical transmission expansion plan, based in the decomposition techniques is presented. The algorithm was used in the Brazilian South System and was able to find an optimal solution, with a low computational resource. Some expansions of this methodology are been investigated: the probabilistic one and the expansion with financier restriction. (C.G.C.). 4 refs, 7 figs

  4. DYNAMIC PROGRAMMING – EFFICIENT TOOL FOR POWER SYSTEM EXPANSION PLANNING

    Directory of Open Access Journals (Sweden)

    SIMO A.

    2015-03-01

    Full Text Available The paper isfocusing on dynamic programming use for power system expansion planning (EP – transmission network (TNEP and distribution network (DNEP. The EP problem has been approached from the retrospective and prospective point of view. To achieve this goal, the authors are developing two software-tools in Matlab environment. Two techniques have been tackled: particle swarm optimization (PSO and genetic algorithms (GA. The case study refers to Test 25 buses test power system developed within the Power Systems Department.

  5. Flight plan optimization

    Science.gov (United States)

    Dharmaseelan, Anoop; Adistambha, Keyne D.

    2015-05-01

    Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra's. Dijkstra's algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

  6. Optimal separable bases and series expansions

    International Nuclear Information System (INIS)

    Poirier, B.

    1997-01-01

    A method is proposed for the efficient calculation of the Green close-quote s functions and eigenstates for quantum systems of two or more dimensions. For a given Hamiltonian, the best possible separable approximation is obtained from the set of all Hilbert-space operators. It is shown that this determination itself, as well as the solution of the resultant approximation, is a problem of reduced dimensionality. Moreover, the approximate eigenstates constitute the optimal separable basis, in the sense of self-consistent field theory. The full solution is obtained from the approximation via iterative expansion. In the time-independent perturbation expansion for instance, all of the first-order energy corrections are zero. In the Green close-quote s function case, we have a distorted-wave Born series with optimized convergence properties. This series may converge even when the usual Born series diverges. Analytical results are presented for an application of the method to the two-dimensional shifted harmonic-oscillator system, in the course of which the quantum tanh 2 potential problem is solved exactly. The universal presence of bound states in the latter is shown to imply long-lived resonances in the former. In a comparison with other theoretical methods, we find that the reaction path Hamiltonian fails to predict such resonances. copyright 1997 The American Physical Society

  7. Generation capacity expansion planning in deregulated electricity markets

    Science.gov (United States)

    Sharma, Deepak

    With increasing demand of electric power in the context of deregulated electricity markets, a good strategic planning for the growth of the power system is critical for our tomorrow. There is a need to build new resources in the form of generation plants and transmission lines while considering the effects of these new resources on power system operations, market economics and the long-term dynamics of the economy. In deregulation, the exercise of generation planning has undergone a paradigm shift. The first stage of generation planning is now undertaken by the individual investors. These investors see investments in generation capacity as an increasing business opportunity because of the increasing market prices. Therefore, the main objective of such a planning exercise, carried out by individual investors, is typically that of long-term profit maximization. This thesis presents some modeling frameworks for generation capacity expansion planning applicable to independent investor firms in the context of power industry deregulation. These modeling frameworks include various technical and financing issues within the process of power system planning. The proposed modeling frameworks consider the long-term decision making process of investor firms, the discrete nature of generation capacity addition and incorporates transmission network modeling. Studies have been carried out to examine the impact of the optimal investment plans on transmission network loadings in the long-run by integrating the generation capacity expansion planning framework within a modified IEEE 30-bus transmission system network. The work assesses the importance of arriving at an optimal IRR at which the firm's profit maximization objective attains an extremum value. The mathematical model is further improved to incorporate binary variables while considering discrete unit sizes, and subsequently to include the detailed transmission network representation. The proposed models are novel in the

  8. Transmission Network Expansion Planning Considering Phase-Shifter Transformers

    Directory of Open Access Journals (Sweden)

    Celso T. Miasaki

    2012-01-01

    Full Text Available This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process.

  9. Sensitivity analysis in electric system expansion planning study using DECADES

    International Nuclear Information System (INIS)

    Perez Martin, D.; Lopez Lopez, I.

    1998-01-01

    To cover the increasing electricity demand as a key economic and social factor of development, it is necessary to have adequate expansion police. The delay in installation of certain capabilities produces electricity deficit. In other hand, construction of oversized capacities generates excessive costs. Therefore it is important to acquire or develop adequate methodologies according to the country specific conditions to carry out electric expansion planning studies. The goal is to chose optimal solutions in order to reach sustainable development using owns energy resources and preserving the environment. In the paper the Decades methodology is used for electricity system expansion planning. Premises and main assumptions for the calculations are presented. Some electric system expansion cases are evaluated. We also present the results of a sensibility study varying the discount rate, loss of load probability energy not served cost, fuel availability and fuel and investment costs. The reliability criteria currently not used in Cuban electric system are evaluated. We discuss the results and display the conclusions and recommendations

  10. Expansion plan of the electrical sector; Plan de expansion del sector electrico

    Energy Technology Data Exchange (ETDEWEB)

    Cristerna Ocampo, Rafael [Comision Federal de Electricidad (Mexico)

    1996-07-01

    An analysis of the Mexican electrical market in the year 1994 as far as sales of electrical energy and types of users who utilized that energy, is presented. In addition, an analysis is made of the options for the future supply, where the installed electrical capacity in Mexico in 1994 is described. Also the requirements of additional capacity of power generation, from year 1995 to year 2004 are analyzed. In the internal supply of primary energy in Mexico, the hydrocarbons represent 83%, the diversified sources (nuclear, geothermal, hydro and coal) represent 7% and the biomass as well as complementary coal, the 10% balance of the primary energy. Finally an expansion plan of the transmission network of the Mexican electrical system is described. [Spanish] Se presenta un analisis del mercado electrico mexicano en el ano de 1994 en cuanto a ventas de energia electrica y los tipos de usuarios que utilizaron esa energia. Se hace un analisis ademas, de las opciones para la oferta futura, donde se describe la capacidad electrica instalada de Mexico en 1994. Tambien se analizan los requerimientos de capacidad adicional de generacion de 1995 al 2004. En la oferta interna de energia primaria en Mexico, los hidrocarburos representan el 83%, las fuentes diversificadas (nuclear, geotermia, hidro y carboelectrica) representan el 7% y la biomasa asi como el carbon complementario, el 10% restante de la energia primaria. Finalmente se describe un plan de expansion de la red de transmision del sistema electrico mexicano.

  11. Studying medium effects with the optimized δ expansion

    International Nuclear Information System (INIS)

    Krein, G.; Menezes, D.P.; Nielsen, M.; Pinto, M.B.

    1995-04-01

    The possibility of using the optimized δ expansion for studying medium effects on hadronic properties in quark or nuclear matter is investigated. The δ expansion is employed to study density effects with two commonly used models in hadron and nuclear physics, the Nambu-Jona-Lasinio model for the dynamical chiral symmetry breaking and the Walecka model for the equation of state of nuclear matter. The results obtained with the δ expansion are compared to those obtained with the traditional Hartree-Fock approximation. Perspectives for using the δ expansion in other field theoretic models in hadron and nuclear physics are discussed. (author). 17 refs, 9 figs

  12. Studying medium effects with the optimized {delta} expansion

    Energy Technology Data Exchange (ETDEWEB)

    Krein, G [Instituto de Fisica Teorica (IFT), Sao Paulo, SP (Brazil); Menezes, D P [Santa Catarina Univ., Florianopolis, SC (Brazil). Dept. de Fisica; Nielsen, M [Sao Paulo Univ., SP (Brazil). Inst. de Fisica; Pinto, M B [Montpellier-2 Univ., 34 (France). Lab. de Physique Mathematique

    1995-04-01

    The possibility of using the optimized {delta} expansion for studying medium effects on hadronic properties in quark or nuclear matter is investigated. The {delta} expansion is employed to study density effects with two commonly used models in hadron and nuclear physics, the Nambu-Jona-Lasinio model for the dynamical chiral symmetry breaking and the Walecka model for the equation of state of nuclear matter. The results obtained with the {delta} expansion are compared to those obtained with the traditional Hartree-Fock approximation. Perspectives for using the {delta} expansion in other field theoretic models in hadron and nuclear physics are discussed. (author). 17 refs, 9 figs.

  13. A multi-objective framework for dynamic transmission expansion planning in competitive electricity market

    International Nuclear Information System (INIS)

    Foroud, Asghar Akbari; Abdoos, Ali Akbar; Keypour, Reza; Amirahmadi, Meisam

    2010-01-01

    Restructuring of power system has changed the traditional planning objectives and introduced challenges in the field of Transmission Expansion Planning (TEP). Due to these changes, new approaches and criteria are needed for transmission planning in deregulated environment. Therefore, in this paper, a dynamic expansion methodology is presented using a multi-objective optimization framework. Investment cost, congestion cost and reliability are considered in the optimization as three objectives. To overcome the difficulties in solving the non-convex and mixed integer nature of the optimization problems, a Non-Dominated Sorting Genetic Algorithm (NSGA II) approach is used followed by a fuzzy decision making analysis to obtain the final optimal solution. The planning methodology has been demonstrated on the IEEE 24-bus test system and north-east of Iran national 400 kV transmission grid to show the feasibility and capabilities of the proposed algorithm in electricity market environment. (author)

  14. Multi criteria analysis for the long term planning of the mexican electrical system expansion - 337

    International Nuclear Information System (INIS)

    Martin-del-Campo, C.; Guadarrama, R.; Francois, J.L.

    2010-01-01

    A multi-criteria analysis was applied to the long term electricity expansion planning for Mexico for the 2008-2030 period. This methodology is based on a fuzzy logic inference system, which allows for the definition of a decision function that takes into account all the evaluation parameters. This function permits one to rank the alternative expansion plans in order to determine the most attractive option. In this study four evaluation parameters were considered: (a) the total generating cost obtained from an optimization expansion using the WASP-IV model, (b) the economic risk associated with fuel prices increases, (c) the diversity of technologies in the mix, and (d) the external costs. The analysis was applied to a base case and to three additional expansion cases, which are very similar to the base case, but each of them excludes the addition of a certain type of candidate technology in the optimization planning. The base case is Plan A which has six candidate technologies available for the optimization planning. Plan B excludes coal; Plan C excludes oil, and Plan D excludes nuclear energy. After the decision analysis was made it was found that Plan B is best followed by Plan A, then Plan C and finally Plan D. The worst plan expansion was obtained when the nuclear candidate was excluded in the program of additions during the time period. The primary conclusion is that nuclear energy must participate in the mix of electricity generation. This result can be used to define the energy policy for electricity production in Mexico in the medium-long term scenario. (authors)

  15. Optimal transmission planning under the Mexican new electricity market

    International Nuclear Information System (INIS)

    Zenón, Eric; Rosellón, Juan

    2017-01-01

    This paper addresses electricity transmission planning under the new industry and institutional structure of the Mexican electricity market, which has engaged in a deep reform process after decades of a state-owned-vertically-integrated-non-competitive-closed industry. Under this new structure, characterized by a nodal pricing system and an independent system operator (ISO), we analyze welfare-optimal network expansion with two modeling strategies. In a first model, we propose the use of an incentive price-cap mechanism to promote the expansion of Mexican networks. In a second model, we study centrally-planned grid expansion in Mexico by an ISO within a power-flow model. We carry out comparisons of these models which provide us with hints to evaluate the actual transmission planning process proposed by Mexican authorities (PRODESEN). We obtain that the PRODESEN plan appears to be a convergent welfare-optimal planning process. - Highlights: • We model transmission planning (PRODESEN) in the Mexican new electricity market. • We propose a first model with a price-cap mechanism to promote network expansion. • In a second power-flow model, we study centrally-planned grid expansions. • The PRODESEN appears to be a convergent welfare-optimal planning process. • Incentive regulation could further help to implement such an optimal process.

  16. 216-B-3 expansion ponds closure plan

    Energy Technology Data Exchange (ETDEWEB)

    1994-10-01

    This document describes the activities for clean closure under the Resource Conservation and Recovery Act of 1976 (RCRA) of the 216-B-3 Expansion Ponds. The 216-B-3 Expansion Ponds are operated by the US Department of Energy, Richland Operations Office (DOE-RL) and co-operated by Westinghouse Hanford Company (Westinghouse Hanford). The 216-B-3 Expansion Ponds consists of a series of three earthen, unlined, interconnected ponds that receive waste water from various 200 East Area operating facilities. The 3A, 3B, and 3C ponds are referred to as Expansion Ponds because they expanded the capability of the B Pond System. Waste water (primarily cooling water, steam condensate, and sanitary water) from various 200 East Area facilities is discharged to the Bypass pipe (Project X-009). Water discharged to the Bypass pipe flows directly into the 216-B-3C Pond. The ponds were operated in a cascade mode, where the Main Pond overflowed into the 3A Pond and the 3A Pond overflowed into the 3C Pond. The 3B Pond has not received waste water since May 1985; however, when in operation, the 3B Pond received overflow from the 3A Pond. In the past, waste water discharges to the Expansion Ponds had the potential to have contained mixed waste (radioactive waste and dangerous waste). The radioactive portion of mixed waste has been interpreted by the US Department of Energy (DOE) to be regulated under the Atomic Energy Act of 1954; the dangerous waste portion of mixed waste is regulated under RCRA.

  17. 216-B-3 expansion ponds closure plan

    International Nuclear Information System (INIS)

    1994-10-01

    This document describes the activities for clean closure under the Resource Conservation and Recovery Act of 1976 (RCRA) of the 216-B-3 Expansion Ponds. The 216-B-3 Expansion Ponds are operated by the US Department of Energy, Richland Operations Office (DOE-RL) and co-operated by Westinghouse Hanford Company (Westinghouse Hanford). The 216-B-3 Expansion Ponds consists of a series of three earthen, unlined, interconnected ponds that receive waste water from various 200 East Area operating facilities. The 3A, 3B, and 3C ponds are referred to as Expansion Ponds because they expanded the capability of the B Pond System. Waste water (primarily cooling water, steam condensate, and sanitary water) from various 200 East Area facilities is discharged to the Bypass pipe (Project X-009). Water discharged to the Bypass pipe flows directly into the 216-B-3C Pond. The ponds were operated in a cascade mode, where the Main Pond overflowed into the 3A Pond and the 3A Pond overflowed into the 3C Pond. The 3B Pond has not received waste water since May 1985; however, when in operation, the 3B Pond received overflow from the 3A Pond. In the past, waste water discharges to the Expansion Ponds had the potential to have contained mixed waste (radioactive waste and dangerous waste). The radioactive portion of mixed waste has been interpreted by the US Department of Energy (DOE) to be regulated under the Atomic Energy Act of 1954; the dangerous waste portion of mixed waste is regulated under RCRA

  18. Multicriteria optimization informed VMAT planning

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Huixiao; Craft, David L.; Gierga, David P., E-mail: dgierga@partners.org

    2014-04-01

    We developed a patient-specific volumetric-modulated arc therapy (VMAT) optimization procedure using dose-volume histogram (DVH) information from multicriteria optimization (MCO) of intensity-modulated radiotherapy (IMRT) plans. The study included 10 patients with prostate cancer undergoing standard fractionation treatment, 10 patients with prostate cancer undergoing hypofractionation treatment, and 5 patients with head/neck cancer. MCO-IMRT plans using 20 and 7 treatment fields were generated for each patient on the RayStation treatment planning system (clinical version 2.5, RaySearch Laboratories, Stockholm, Sweden). The resulting DVH of the 20-field MCO-IMRT plan for each patient was used as the reference DVH, and the extracted point values of the resulting DVH of the MCO-IMRT plan were used as objectives and constraints for VMAT optimization. Weights of objectives or constraints of VMAT optimization or both were further tuned to generate the best match with the reference DVH of the MCO-IMRT plan. The final optimal VMAT plan quality was evaluated by comparison with MCO-IMRT plans based on homogeneity index, conformity number of planning target volume, and organ at risk sparing. The influence of gantry spacing, arc number, and delivery time on VMAT plan quality for different tumor sites was also evaluated. The resulting VMAT plan quality essentially matched the 20-field MCO-IMRT plan but with a shorter delivery time and less monitor units. VMAT plan quality of head/neck cancer cases improved using dual arcs whereas prostate cases did not. VMAT plan quality was improved by fine gantry spacing of 2 for the head/neck cancer cases and the hypofractionation-treated prostate cancer cases but not for the standard fractionation–treated prostate cancer cases. MCO-informed VMAT optimization is a useful and valuable way to generate patient-specific optimal VMAT plans, though modification of the weights of objectives or constraints extracted from resulting DVH of MCO

  19. Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Ding, Yi; Wu, Qiuwei

    2013-01-01

    This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO...... algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified...

  20. 2015 Plan. Project 1: methodology and planning process of the Brazilian electric sector expansion

    International Nuclear Information System (INIS)

    1993-10-01

    The Planning Process of Brazilian Electric Sector Expansion, their normative aspects, instruments, main agents and the planning cycles are described. The methodology of expansion planning is shown, with the interactions of several study areas, electric power market and the used computer models. The forecasts of methodology evolution is also presented. (C.G.C.)

  1. Interactively exploring optimized treatment plans

    International Nuclear Information System (INIS)

    Rosen, Isaac; Liu, H. Helen; Childress, Nathan; Liao Zhongxing

    2005-01-01

    Purpose: A new paradigm for treatment planning is proposed that embodies the concept of interactively exploring the space of optimized plans. In this approach, treatment planning ignores the details of individual plans and instead presents the physician with clinical summaries of sets of solutions to well-defined clinical goals in which every solution has been optimized in advance by computer algorithms. Methods and materials: Before interactive planning, sets of optimized plans are created for a variety of treatment delivery options and critical structure dose-volume constraints. Then, the dose-volume parameters of the optimized plans are fit to linear functions. These linear functions are used to show in real time how the target dose-volume histogram (DVH) changes as the DVHs of the critical structures are changed interactively. A bitmap of the space of optimized plans is used to restrict the feasible solutions. The physician selects the critical structure dose-volume constraints that give the desired dose to the planning target volume (PTV) and then those constraints are used to create the corresponding optimized plan. Results: The method is demonstrated using prototype software, Treatment Plan Explorer (TPEx), and a clinical example of a patient with a tumor in the right lung. For this example, the delivery options included 4 open beams, 12 open beams, 4 wedged beams, and 12 wedged beams. Beam directions and relative weights were optimized for a range of critical structure dose-volume constraints for the lungs and esophagus. Cord dose was restricted to 45 Gy. Using the interactive interface, the physician explored how the tumor dose changed as critical structure dose-volume constraints were tightened or relaxed and selected the best compromise for each delivery option. The corresponding treatment plans were calculated and compared with the linear parameterization presented to the physician in TPEx. The linear fits were best for the maximum PTV dose and worst

  2. IRP methods for Environmental Impact Statements of utility expansion plans

    International Nuclear Information System (INIS)

    Cavallo, J.D.; Hemphill, R.C.; Veselka, T.D.

    1992-01-01

    Most large electric utilities and a growing number of gas utilities in the United States are using a planning method -- Integrated Resource Planning (IRP) - which incorporates demand-side management (DSM) programs whenever the marginal cost of the DSM programs are lower than the marginal cost of supply-side expansion options. Argonne National Laboratory has applied the IRP method in its socio-economic analysis of an Environmental Impact Statement (EIS) of power marketing for a system of electric utilities in the mountain and western regions of the United States. Applying the IRP methods provides valuable information to the participants in an EIS process involving capacity expansion of an electric or gas utility. The major challenges of applying the IRP method within an EIS are the time consuming and costly task of developing a least cost expansion path for each altemative, the detailed quantification of environmental damages associated with capacity expansion, and the explicit inclusion of societal-impacts to the region

  3. Multi-year expansion planning of large transmission networks

    Energy Technology Data Exchange (ETDEWEB)

    Binato, S; Oliveira, G C [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil)

    1994-12-31

    This paper describes a model for multi-year transmission network expansion to be used in long-term system planning. The network is represented by a linearized (DC) power flow and, for each year, operation costs are evaluated by a linear programming (LP) based algorithm that provides sensitivity indices for circuit reinforcements. A Backward/Forward approaches is proposed to devise an expansion plan over the study period. A case study with the southeastern Brazilian system is presented and discussed. (author) 18 refs., 5 figs., 1 tab.

  4. British Gas plans global gas unit expansion

    International Nuclear Information System (INIS)

    Vielvoye, R.

    1991-01-01

    This paper reports on developing a global gas business, a British Gas plc's strategy for evolving a state owned U.K. gas company to a privatized worldwide oil and gas giant. By 2000, BG's global gas business is expected to provide 20% of its revenues, compared with 40% each from its exploration and production operations and its U.K. gas business. The global gas unit (GGU) plans to meet its targets mainly through acquiring holdings in gas transmission and distribution companies around the world. In the 12 months since GGU was established, it has made two such major acquisitions in this area. BG acquired Consumers Gas Co., Ltd., Ontario, Canada's biggest natural gas distribution company, for $943.5 million. It also took a 10% stake in Catalana de Gas SA, Barcelona, the largest privately owned gas utility in Spain and in terms of number of customers, the fourth largest in western Europe. BG also is targeting additional revenues from developing gas fired cogeneration systems in developing countries with gas reserves but no established transmission and distribution systems

  5. Multistage and multiobjective formulations of globally optimal upgradable expansions for electric power distribution systems

    Science.gov (United States)

    Vaziri Yazdi Pin, Mohammad

    Electric power distribution systems are the last high voltage link in the chain of production, transport, and delivery of the electric energy, the fundamental goals of which are to supply the users' demand safely, reliably, and economically. The number circuit miles traversed by distribution feeders in the form of visible overhead or imbedded underground lines, far exceed those of all other bulk transport circuitry in the transmission system. Development and expansion of the distribution systems, similar to other systems, is directly proportional to the growth in demand and requires careful planning. While growth of electric demand has recently slowed through efforts in the area of energy management, the need for a continued expansion seems inevitable for the near future. Distribution system and expansions are also independent of current issues facing both the suppliers and the consumers of electrical energy. For example, deregulation, as an attempt to promote competition by giving more choices to the consumers, while it will impact the suppliers' planning strategies, it cannot limit the demand growth or the system expansion in the global sense. Curiously, despite presence of technological advancements and a 40-year history of contributions in the area, many of the major utilities still relay on experience and resort to rudimentary techniques when planning expansions. A comprehensive literature review of the contributions and careful analyses of the proposed algorithms for distribution expansion, confirmed that the problem is a complex, multistage and multiobjective problem for which a practical solution remains to be developed. In this research, based on the 15-year experience of a utility engineer, the practical expansion problem has been clearly defined and the existing deficiencies in the previous work identified and analyzed. The expansion problem has been formulated as a multistage planning problem in line with a natural course of development and industry

  6. A new evolutionary solution method for dynamic expansion planning of DG-integrated primary distribution networks

    International Nuclear Information System (INIS)

    Ahmadigorji, Masoud; Amjady, Nima

    2014-01-01

    Highlights: • A new dynamic distribution network expansion planning model is presented. • A Binary Enhanced Particle Swarm Optimization (BEPSO) algorithm is proposed. • A Modified Differential Evolution (MDE) algorithm is proposed. • A new bi-level optimization approach composed of BEPSO and MDE is presented. • The effectiveness of the proposed optimization approach is extensively illustrated. - Abstract: Reconstruction in the power system and appearing of new technologies for generation capacity of electrical energy has led to significant innovation in Distribution Network Expansion Planning (DNEP). Distributed Generation (DG) includes the application of small/medium generation units located in power distribution networks and/or near the load centers. Appropriate utilization of DG can affect the various technical and operational indices of the distribution network such as the feeder loading, energy losses and voltage profile. In addition, application of DG in proper size is an essential tool to achieve the DG maximum potential benefits. In this paper, a time-based (dynamic) model for DNEP is proposed to determine the optimal size, location and installation year of DG in distribution system. Also, in this model, the Optimal Power Flow (OPF) is exerted to determine the optimal generation of DGs for every potential solution in order to minimize the investment and operation costs following the load growth in a specified planning period. Besides, the reinforcement requirements of existing distribution feeders are considered, simultaneously. The proposed optimization problem is solved by the combination of evolutionary methods of a new Binary Enhanced Particle Swarm Optimization (BEPSO) and Modified Differential Evolution (MDE) to find the optimal expansion strategy and solve OPF, respectively. The proposed planning approach is applied to two typical primary distribution networks and compared with several other methods. These comparisons illustrate the

  7. Biocapacity optimization in regional planning

    Science.gov (United States)

    Guo, Jianjun; Yue, Dongxia; Li, Kai; Hui, Cang

    2017-01-01

    Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention.

  8. Global Optimization for Transport Network Expansion and Signal Setting

    OpenAIRE

    Liu, Haoxiang; Wang, David Z. W.; Yue, Hao

    2015-01-01

    This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two pr...

  9. Design of materials with extreme thermal expansion using a three-phase topology optimization method

    DEFF Research Database (Denmark)

    Sigmund, Ole; Torquato, S.

    1997-01-01

    Composites with extremal or unusual thermal expansion coefficients are designed using a three-phase topology optimization method. The composites are made of two different material phases and a void phase. The topology optimization method consists in finding the distribution of material phases...... materials having maximum directional thermal expansion (thermal actuators), zero isotropic thermal expansion, and negative isotropic thermal expansion. It is shown that materials with effective negative thermal expansion coefficients can be obtained by mixing two phases with positive thermal expansion...

  10. Generation Expansion Planning With Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

    Energy Technology Data Exchange (ETDEWEB)

    Zhan, Yiduo; Zheng, Qipeng P.; Wang, Jianhui; Pinson, Pierre

    2017-07-01

    Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of wind power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.

  11. Optimized t-expansion method for the Rabi Hamiltonian

    International Nuclear Information System (INIS)

    Travenec, Igor; Samaj, Ladislav

    2011-01-01

    A polemic arose recently about the applicability of the t-expansion method to the calculation of the ground state energy E 0 of the Rabi model. For specific choices of the trial function and very large number of involved connected moments, the t-expansion results are rather poor and exhibit considerable oscillations. In this Letter, we formulate the t-expansion method for trial functions containing two free parameters which capture two exactly solvable limits of the Rabi Hamiltonian. At each order of the t-series, E 0 is assumed to be stationary with respect to the free parameters. A high accuracy of E 0 estimates is achieved for small numbers (5 or 6) of involved connected moments, the relative error being smaller than 10 -4 (0.01%) within the whole parameter space of the Rabi Hamiltonian. A special symmetrization of the trial function enables us to calculate also the first excited energy E 1 , with the relative error smaller than 10 -2 (1%). -- Highlights: → We study the ground state energy of the Rabi Hamiltonian. → We use the t-expansion method with an optimized trial function. → High accuracy of estimates is achieved, the relative error being smaller than 0.01%. → The calculation of the first excited state energy is made. The method has a general applicability.

  12. Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Ameli

    2012-01-01

    Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.

  13. Combined heuristic with fuzzy system to transmission system expansion planning

    Energy Technology Data Exchange (ETDEWEB)

    Silva Sousa, Aldir; Asada, Eduardo N. [University of Sao Paulo, Sao Carlos School of Engineering, Department of Electrical Engineering Av. Trabalhador Sao-carlense, 400, 13566-590 Sao Carlos, SP (Brazil)

    2011-01-15

    A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (author)

  14. Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Tekiner, Hatice [Industrial Engineering, College of Engineering and Natural Sciences, Istanbul Sehir University, 2 Ahmet Bayman Rd, Istanbul (Turkey); Coit, David W. [Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Rd., Piscataway, NJ (United States); Felder, Frank A. [Edward J. Bloustein School of Planning and Public Policy, Rutgers University, Piscataway, NJ (United States)

    2010-12-15

    A new approach to the electricity generation expansion problem is proposed to minimize simultaneously multiple objectives, such as cost and air emissions, including CO{sub 2} and NO{sub x}, over a long term planning horizon. In this problem, system expansion decisions are made to select the type of power generation, such as coal, nuclear, wind, etc., where the new generation asset should be located, and at which time period expansion should take place. We are able to find a Pareto front for the multi-objective generation expansion planning problem that explicitly considers availability of the system components over the planning horizon and operational dispatching decisions. Monte-Carlo simulation is used to generate numerous scenarios based on the component availabilities and anticipated demand for energy. The problem is then formulated as a mixed integer linear program, and optimal solutions are found based on the simulated scenarios with a combined objective function considering the multiple problem objectives. The different objectives are combined using dimensionless weights and a Pareto front can be determined by varying these weights. The mathematical model is demonstrated on an example problem with interesting results indicating how expansion decisions vary depending on whether minimizing cost or minimizing greenhouse gas emissions or pollutants is given higher priority. (author)

  15. A multi-stage stochastic transmission expansion planning method

    International Nuclear Information System (INIS)

    Akbari, Tohid; Rahimikian, Ashkan; Kazemi, Ahad

    2011-01-01

    Highlights: → We model a multi-stage stochastic transmission expansion planning problem. → We include available transfer capability (ATC) in our model. → Involving this criterion will increase the ATC between source and sink points. → Power system reliability will be increased and more money can be saved. - Abstract: This paper presents a multi-stage stochastic model for short-term transmission expansion planning considering the available transfer capability (ATC). The ATC can have a huge impact on the power market outcomes and the power system reliability. The transmission expansion planning (TEP) studies deal with many uncertainties, such as system load uncertainties that are considered in this paper. The Monte Carlo simulation method has been applied for generating different scenarios. A scenario reduction technique is used for reducing the number of scenarios. The objective is to minimize the sum of investment costs (IC) and the expected operation costs (OC). The solution technique is based on the benders decomposition algorithm. The N-1 contingency analysis is also done for the TEP problem. The proposed model is applied to the IEEE 24 bus reliability test system and the results are efficient and promising.

  16. Electric utility resource expansion planning using environmental externalities

    International Nuclear Information System (INIS)

    Mitchell, D.

    1992-01-01

    This paper describes the recent experience of San Diego Gas ampersand Electric Company using environmental externalities in the expansion planning of its electrical system. This is the first time that this method of planning has been used in the electric utility industry in California. The paper reviews the conceptual development of the monetary values for environmental externalities and shows how the application of these values modifies the resource selection process. This paper should be of interest to professionals involved in policy issues relating to the use of environmental externalities as a means to improve the environment. The experience gained through this analyses should also benefit electric utility personnel involved in planning, and regulators interested in planning

  17. Technical and economic evaluation of voltage level in transmission network expansion planning using GA

    International Nuclear Information System (INIS)

    Jalilzadeh, S.; Kazemi, A.; Shayeghi, H.; Madavi, M.

    2008-01-01

    Transmission network expansion planning is an important part of power system planning. Its task is to determine an optimal network configuration according to load growth. It determines where, when and how many new transmission lines should be installed. Up to now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem, but in all of these methods, the STNEP problem has been solved regardless of voltage level of the lines. In this paper, due to different voltage levels in the transmission network, which cause different annual losses, STNEP has been studied considering the voltage level of the transmission lines and the network loss using the genetic algorithm (GA). Finally, the proposed idea has been examined on Garvers 6 bus network. The results show that considering the loss in a network with different voltage levels decreases the operational costs considerably, and the network satisfies the requirement of delivering electric power more safely and reliably to load centers

  18. Reliability constrained generation expansion planning with consideration of wind farms uncertainties in deregulated electricity market

    International Nuclear Information System (INIS)

    Hemmati, Reza; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin

    2013-01-01

    Highlights: • Generation expansion planning is presented in deregulated electricity market. • Wind farm uncertainty is modeled in the problem. • The profit of each GENCO is maximized and also the safe operation of system is satisfied. • Salve sector is managed as an optimization programming and solved by using PSO technique. • Master sector is considered in pool market and Cournot model is used to simulate it. - Abstract: This paper addresses reliability constrained generation expansion planning (GEP) in the presence of wind farm uncertainty in deregulated electricity market. The proposed GEP aims at maximizing the expected profit of all generation companies (GENCOs), while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). Wind farm uncertainty is also considered in the planning and GENCOs denote their planning in the presence of wind farm uncertainty. The uncertainty is modeled by probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert uncertainty into the problem. The proposed GEP is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. In this paper, Electricity market structure is modeled as a pool market. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs profit in the presence of wind farms uncertainties in electricity market

  19. Optimization of urban water supply portfolios combining infrastructure capacity expansion and water use decisions

    Science.gov (United States)

    Medellin-Azuara, J.; Fraga, C. C. S.; Marques, G.; Mendes, C. A.

    2015-12-01

    The expansion and operation of urban water supply systems under rapidly growing demands, hydrologic uncertainty, and scarce water supplies requires a strategic combination of various supply sources for added reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources merits decisions of what and when to expand, and how much to use of each available sources accounting for interest rates, economies of scale and hydrologic variability. The present research provides a framework and an integrated methodology that optimizes the expansion of various water supply alternatives using dynamic programming and combining both short term and long term optimization of water use and simulation of water allocation. A case study in Bahia Do Rio Dos Sinos in Southern Brazil is presented. The framework couples an optimization model with quadratic programming model in GAMS with WEAP, a rain runoff simulation models that hosts the water supply infrastructure features and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions and (b) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion. Results also highlight the potential of various water supply alternatives including, conservation, groundwater, and infrastructural enhancements over time. The framework proves its usefulness for planning its transferability to similarly urbanized systems.

  20. Decenal plan of electric energy expansion - 2006-2015

    International Nuclear Information System (INIS)

    2006-01-01

    This report is divided into seven chapters and presents: 1) Introduction - a brief description of the institutional context of the study and the decenal planning role in this context; 2) electric power market - the evolution of market and economy conjuncture of electric power and the basic premises for the market projections, including the considered macroeconomic scenery description; 3) electric power generation - considered premises, methodology and criteria for the formulation and adjustment of generation expansion alternatives of electric power; 4) electric power transmission - main aspects which guided the evolution of the interlinked system reference configuration in the decenal period and a description of the main result of transmission system expansion analysis, consolidated by SIN geoelectric region and by each state of these regions; 5) socioenvironmental analysis - adopted methodology and the results of the socioenvironmental analysis for the foreseen business in the decenal horizon; 6) expansion indicators of the electric system - synthesizes the main indicators referring to the decenal period as far the market evolution, generation expansion and transmission is concerned; 7)bibliographic references

  1. Decenal plan of electric energy expansion - 2006-2015

    International Nuclear Information System (INIS)

    2005-01-01

    This report is divided into seven chapters and presents: 1) Introduction - a brief description of the institutional context of the study and the decenal planning role in this context; 2) electric power market - the evolution of market and economy conjuncture of electric power and the basic premises for the market projections, including the considered macroeconomic scenery description; 3) electric power generation - considered premises, methodology and criteria for the formulation and adjustment of generation expansion alternatives of electric power; 4) electric power transmission - main aspects which guided the evolution of the interlinked system reference configuration in the decenal period and a description of the main result of transmission system expansion analysis, consolidated by SIN geoelectric region and by each state of these regions; 5) socioenvironmental analysis - adopted methodology and the results of the socioenvironmental analysis for the foreseen business in the decenal horizon; 6) expansion indicators of the electric system - synthesizes the main indicators referring to the decenal period as far the market evolution, generation expansion and transmission is concerned; 7)bibliographic references

  2. An investigation of the effect of changes of planning criteria on power system expansion planning with a case study of the Jordanian power system

    International Nuclear Information System (INIS)

    Elkarmi, Fawwaz; Abu-Shikhah, Nazih; Abu-Zarour, Mohammad

    2010-01-01

    Many factors contribute to the planning process of power systems. In the context of expansion planning, focus is paid to selection criteria that enable the optimization of related factors that will result in the best performance. This is described as meeting demand whilst reducing costs and maintaining minimal risk in operation. In this paper, different criteria used in the planning of power system expansion studies are investigated with the objective of identifying their impact on the expansion plan. The results of these criteria on the expansion study of the Jordanian power system are presented. Results show good correspondence to the actual adopted solutions. The spinning reserve is the most influential planning criterion on the overall system expansion cost. This is followed by the peak load changes, and the forced outage rate of the candidate units used for capacity additions to meet future expected demand. Finally, the loss of load expectation and cost of energy not served have the least effect on the overall system expansion cost. These results highlight the importance to be placed on performing sensitivity analyses to determine the most cost effective and acceptable expansion plan of the electric power system. There is a need to continually update the planning criteria to cater for changes and developments in the power system and the economic situation. Finally, the methodology of this study can be generalized to other power systems.

  3. An investigation of the effect of changes of planning criteria on power system expansion planning with a case study of the Jordanian power system

    Energy Technology Data Exchange (ETDEWEB)

    Elkarmi, Fawwaz; Abu-Shikhah, Nazih [Al-Ahliyya Amman University, College of Engineering, AA University Post Office, Zip code 19328 (Jordan); Abu-Zarour, Mohammad [NEPCO, Department of Generation Planning, P.O. Box 2310, Amman 11194 (Jordan)

    2010-10-15

    Many factors contribute to the planning process of power systems. In the context of expansion planning, focus is paid to selection criteria that enable the optimization of related factors that will result in the best performance. This is described as meeting demand whilst reducing costs and maintaining minimal risk in operation. In this paper, different criteria used in the planning of power system expansion studies are investigated with the objective of identifying their impact on the expansion plan. The results of these criteria on the expansion study of the Jordanian power system are presented. Results show good correspondence to the actual adopted solutions. The spinning reserve is the most influential planning criterion on the overall system expansion cost. This is followed by the peak load changes, and the forced outage rate of the candidate units used for capacity additions to meet future expected demand. Finally, the loss of load expectation and cost of energy not served have the least effect on the overall system expansion cost. These results highlight the importance to be placed on performing sensitivity analyses to determine the most cost effective and acceptable expansion plan of the electric power system. There is a need to continually update the planning criteria to cater for changes and developments in the power system and the economic situation. Finally, the methodology of this study can be generalized to other power systems. (author)

  4. Schedule optimization study implementation plan

    International Nuclear Information System (INIS)

    1993-11-01

    This Implementation Plan is intended to provide a basis for improvements in the conduct of the Environmental Restoration (ER) Program at Hanford. The Plan is based on the findings of the Schedule Optimization Study (SOS) team which was convened for two weeks in September 1992 at the request of the U.S. Department of Energy (DOE) Richland Operations Office (RL). The need for the study arose out of a schedule dispute regarding the submission of the 1100-EM-1 Operable Unit (OU) Remedial Investigation/Feasibility Study (RI/FS) Work Plan. The SOS team was comprised of independent professionals from other federal agencies and the private sector experienced in environmental restoration within the federal system. The objective of the team was to examine reasons for the lengthy RI/FS process and recommend ways to expedite it. The SOS team issued their Final Report in December 1992. The report found the most serious impediments to cleanup relate to a series of management and policy issues which are within the control of the three parties managing and monitoring Hanford -- the DOE, U.S. Environmental Protection Agency (EPA), and the State of Washington Department of Ecology (Ecology). The SOS Report identified the following eight cross-cutting issues as the root of major impediments to the Hanford Site cleanup. Each of these eight issues is quoted from the SOS Report followed by a brief, general description of the proposed approach being developed

  5. Optimization design of energy deposition on single expansion ramp nozzle

    Science.gov (United States)

    Ju, Shengjun; Yan, Chao; Wang, Xiaoyong; Qin, Yupei; Ye, Zhifei

    2017-11-01

    Optimization design has been widely used in the aerodynamic design process of scramjets. The single expansion ramp nozzle is an important component for scramjets to produces most of thrust force. A new concept of increasing the aerodynamics of the scramjet nozzle with energy deposition is presented. The essence of the method is to create a heated region in the inner flow field of the scramjet nozzle. In the current study, the two-dimensional coupled implicit compressible Reynolds Averaged Navier-Stokes and Menter's shear stress transport turbulence model have been applied to numerically simulate the flow fields of the single expansion ramp nozzle with and without energy deposition. The numerical results show that the proposal of energy deposition can be an effective method to increase force characteristics of the scramjet nozzle, the thrust coefficient CT increase by 6.94% and lift coefficient CN decrease by 26.89%. Further, the non-dominated sorting genetic algorithm coupled with the Radial Basis Function neural network surrogate model has been employed to determine optimum location and density of the energy deposition. The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method. The optimized thrust coefficient CT further increase by 1.94%, meanwhile, the optimized lift coefficient CN further decrease by 15.02% respectively. At the same time, the optimized performances are in good and reasonable agreement with the numerical predictions. The findings suggest that scramjet nozzle design and performance can benefit from the application of energy deposition.

  6. A fuzzy approach to the generation expansion planning problem in a multi-objective environment

    International Nuclear Information System (INIS)

    Abass, S. A.; Massoud, E. M. A.; Abass, S. A.)

    2007-01-01

    In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. (author)

  7. Optimal planning of integrated multi-energy systems

    DEFF Research Database (Denmark)

    van Beuzekom, I.; Gibescu, M.; Pinson, Pierre

    2017-01-01

    In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration...... and sustainability goals for 2030 and 2045. Optimal green- and brownfield designs for a district's future integrated energy system are compared using a one-step, as well as a two-step planning approach. As expected, the greenfield designs are more cost efficient, as their results are not constrained by the existing...

  8. Grid Transmission Expansion Planning Model Based on Grid Vulnerability

    Science.gov (United States)

    Tang, Quan; Wang, Xi; Li, Ting; Zhang, Quanming; Zhang, Hongli; Li, Huaqiang

    2018-03-01

    Based on grid vulnerability and uniformity theory, proposed global network structure and state vulnerability factor model used to measure different grid models. established a multi-objective power grid planning model which considering the global power network vulnerability, economy and grid security constraint. Using improved chaos crossover and mutation genetic algorithm to optimize the optimal plan. For the problem of multi-objective optimization, dimension is not uniform, the weight is not easy given. Using principal component analysis (PCA) method to comprehensive assessment of the population every generation, make the results more objective and credible assessment. the feasibility and effectiveness of the proposed model are validated by simulation results of Garver-6 bus system and Garver-18 bus.

  9. Impact of forecast errors on expansion planning of power systems with a renewables target

    DEFF Research Database (Denmark)

    Pineda, Salvador; Morales González, Juan Miguel; Boomsma, Trine Krogh

    2015-01-01

    This paper analyzes the impact of production forecast errors on the expansion planning of a power system and investigates the influence of market design to facilitate the integration of renewable generation. For this purpose, we propose a programming modeling framework to determine the generation...... and transmission expansion plan that minimizes system-wide investment and operating costs, while ensuring a given share of renewable generation in the electricity supply. Unlike existing ones, this framework includes both a day-ahead and a balancing market so as to capture the impact of both production forecasts...... and the associated prediction errors. Within this framework, we consider two paradigmatic market designs that essentially differ in whether the day-ahead generation schedule and the subsequent balancing re-dispatch are co-optimized or not. The main features and results of the model set-ups are discussed using...

  10. Optimized electricity expansions with external costs internalized and risk of severe accidents as a new criterion in the decision analysis

    Energy Technology Data Exchange (ETDEWEB)

    Martin del Campo M, C.; Estrada S, G. J., E-mail: cmcm@fi-b.unam.mx [UNAM, Facultad de Ingenieria, Departamento de Sistemas Energeticos, Paseo Cuauhnahuac 8532, 62550 Jiutepec, Morelos (Mexico)

    2011-11-15

    The external cost of severe accidents was incorporated as a new element for the assessment of energy technologies in the expansion plans of the Mexican electric generating system. Optimizations of the electric expansions were made by internalizing the external cost into the objective function of the WASP-IV model as a variable cost, and these expansions were compared with the expansion plans that did not internalize them. Average external costs reported by the Extern E Project were used for each type of technology and were added to the variable component of operation and maintenance cost in the study cases in which the externalises were internalized. Special attention was paid to study the convenience of including nuclear energy in the generating mix. The comparative assessment of six expansion plans was made by means of the Position Vector of Minimum Regret Analysis (PVMRA) decision analysis tool. The expansion plans were ranked according to seven decision criteria which consider internal costs, economical impact associated with incremental fuel prices, diversity, external costs, foreign capital fraction, carbon-free fraction, and external costs of severe accidents. A set of data for the calculation of the last criterion was obtained from a Report of the European Commission. We found that with the external costs included in the optimization process of WASP-IV, better electric expansion plans, with lower total (internal + external) generating costs, were found. On the other hand, the plans which included the participation of nuclear power plants were in general relatively more attractive than the plans that did not. (Author)

  11. Automatic Planning of External Search Engine Optimization

    Directory of Open Access Journals (Sweden)

    Vita Jasevičiūtė

    2015-07-01

    Full Text Available This paper describes an investigation of the external search engine optimization (SEO action planning tool, dedicated to automatically extract a small set of most important keywords for each month during whole year period. The keywords in the set are extracted accordingly to external measured parameters, such as average number of searches during the year and for every month individually. Additionally the position of the optimized web site for each keyword is taken into account. The generated optimization plan is similar to the optimization plans prepared manually by the SEO professionals and can be successfully used as a support tool for web site search engine optimization.

  12. Simultaneous optimization of sequential IMRT plans

    International Nuclear Information System (INIS)

    Popple, Richard A.; Prellop, Perri B.; Spencer, Sharon A.; Santos, Jennifer F. de los; Duan, Jun; Fiveash, John B.; Brezovich, Ivan A.

    2005-01-01

    Radiotherapy often comprises two phases, in which irradiation of a volume at risk for microscopic disease is followed by a sequential dose escalation to a smaller volume either at a higher risk for microscopic disease or containing only gross disease. This technique is difficult to implement with intensity modulated radiotherapy, as the tolerance doses of critical structures must be respected over the sum of the two plans. Techniques that include an integrated boost have been proposed to address this problem. However, clinical experience with such techniques is limited, and many clinicians are uncomfortable prescribing nonconventional fractionation schemes. To solve this problem, we developed an optimization technique that simultaneously generates sequential initial and boost IMRT plans. We have developed an optimization tool that uses a commercial treatment planning system (TPS) and a high level programming language for technical computing. The tool uses the TPS to calculate the dose deposition coefficients (DDCs) for optimization. The DDCs were imported into external software and the treatment ports duplicated to create the boost plan. The initial, boost, and tolerance doses were specified and used to construct cost functions. The initial and boost plans were optimized simultaneously using a gradient search technique. Following optimization, the fluence maps were exported to the TPS for dose calculation. Seven patients treated using sequential techniques were selected from our clinical database. The initial and boost plans used to treat these patients were developed independently of each other by dividing the tolerance doses proportionally between the initial and boost plans and then iteratively optimizing the plans until a summation that met the treatment goals was obtained. We used the simultaneous optimization technique to generate plans that met the original planning goals. The coverage of the initial and boost target volumes in the simultaneously optimized

  13. Energy efficiency resource modeling in generation expansion planning

    International Nuclear Information System (INIS)

    Ghaderi, A.; Parsa Moghaddam, M.; Sheikh-El-Eslami, M.K.

    2014-01-01

    Energy efficiency plays an important role in mitigating energy security risks and emission problems. In this paper, energy efficiency resources are modeled as efficiency power plants (EPP) to evaluate their impacts on generation expansion planning (GEP). The supply curve of EPP is proposed using the production function of electricity consumption. A decision making framework is also presented to include EPP in GEP problem from an investor's point of view. The revenue of EPP investor is obtained from energy cost reduction of consumers and does not earn any income from electricity market. In each stage of GEP, a bi-level model for operation problem is suggested: the upper-level represents profit maximization of EPP investor and the lower-level corresponds to maximize the social welfare. To solve the bi-level problem, a fixed-point iteration algorithm is used known as diagonalization method. Energy efficiency feed-in tariff is investigated as a regulatory support scheme to encourage the investor. Results pertaining to a case study are simulated and discussed. - Highlights: • An economic model for energy efficiency programs is presented. • A framework is provided to model energy efficiency resources in GEP problem. • FIT is investigated as a regulatory support scheme to encourage the EPP investor. • The capacity expansion is delayed and reduced with considering EPP in GEP. • FIT-II can more effectively increase the energy saving compared to FIT-I

  14. Market-based transmission expansion planning by improved differential evolution

    International Nuclear Information System (INIS)

    Georgilakis, Pavlos S.

    2010-01-01

    The restructuring and deregulation has exposed the transmission planner to new objectives and uncertainties. As a result, new criteria and approaches are needed for transmission expansion planning (TEP) in deregulated electricity markets. This paper proposes a new market-based approach for TEP. An improved differential evolution (IDE) model is proposed for the solution of this new market-based TEP problem. The modifications of IDE in comparison to the simple differential evolution method are: (1) the scaling factor F is varied randomly within some range, (2) an auxiliary set is employed to enhance the diversity of the population, (3) the newly generated trial vector is compared with the nearest parent, and (4) the simple feasibility rule is used to treat the constraints. Results from the application of the proposed method on the IEEE 30-bus test system demonstrate the feasibility and practicality of the proposed IDE for the solution of TEP problem. (author)

  15. Development of a regional capacity expansion plan in the Russian Federation. Application of the WASP Model

    International Nuclear Information System (INIS)

    Chernilin, Yu.; Kononov, S.; Zakharova, E.; Kagramanyan, V.; Malenkov, A.

    1997-01-01

    The Wien Automatic System Planning Package (WASP) is used for the development of optimal capacity expansion plans in Russia. The object of the WASP study is the Central power pool, which is the largest power pool in Russia and has an essential share of nuclear power in electricity generation. The objective of the study is to assess the long-term competitiveness of nuclear power in the region. The major features of the power system analyzed with WASP are the following: 1) four types of electricity generators are considered: condensity fossil fuel plants, cogeneration fossil fuel plants, nuclear power plants and hydraulic plants; 2) nine fuel categories are considered: gas/fuel oil fuel, several types of coal and several nuclear fuels; 3) escalation of capital, operation and maintenance, and fuel costs as a result of economic transition is explicitly modeled. Under these assumptions, a regional optimal capacity expansion plan is developed that showed the following: (a) Until 2004 there is no need for new electricity generation capacities due to the drop in demand in the 90s, certain lifetime margin of existing capacities, committed additions of co-generators and planned refurbishment/repowering measures; (b) The structure of the optimal capacity mix confirms that nuclear power can retain its role as one of the major electricity generation sources in the region. The most important factor with a positive of effect upon the competitiveness of nuclear power plants is the projected escalation of the prices of fossil fuels; (c) The application of WASP has proved that the model can serve as a valuable planning tool at the power pool level in Russia. (author). 14 refs, 8 figs, 10 tabs

  16. Development of a regional capacity expansion plan in the Russian Federation. Application of the WASP Model

    Energy Technology Data Exchange (ETDEWEB)

    Chernilin, Yu; Kononov, S; Zakharova, E [Russian Research Inst. ` ` Kurchatov Inst.` ` , Moscow (Russian Federation); Kagramanyan, V; Malenkov, A [Institute of Physics and Power Engineering, Obninsk (Russian Federation)

    1997-09-01

    The Wien Automatic System Planning Package (WASP) is used for the development of optimal capacity expansion plans in Russia. The object of the WASP study is the Central power pool, which is the largest power pool in Russia and has an essential share of nuclear power in electricity generation. The objective of the study is to assess the long-term competitiveness of nuclear power in the region. The major features of the power system analyzed with WASP are the following: 1) four types of electricity generators are considered: condensity fossil fuel plants, cogeneration fossil fuel plants, nuclear power plants and hydraulic plants; 2) nine fuel categories are considered: gas/fuel oil fuel, several types of coal and several nuclear fuels; 3) escalation of capital, operation and maintenance, and fuel costs as a result of economic transition is explicitly modeled. Under these assumptions, a regional optimal capacity expansion plan is developed that showed the following: (a) Until 2004 there is no need for new electricity generation capacities due to the drop in demand in the 90s, certain lifetime margin of existing capacities, committed additions of co-generators and planned refurbishment/repowering measures; (b) The structure of the optimal capacity mix confirms that nuclear power can retain its role as one of the major electricity generation sources in the region. The most important factor with a positive of effect upon the competitiveness of nuclear power plants is the projected escalation of the prices of fossil fuels; (c) The application of WASP has proved that the model can serve as a valuable planning tool at the power pool level in Russia. (author). 14 refs, 8 figs, 10 tabs.

  17. Cost estimation of sumatra electricity expansion planning with nuclear option

    International Nuclear Information System (INIS)

    Edwaren Liun

    2008-01-01

    The objective of the study is to obtain the cost analysis on optimum solution of Sumatra electricity system using WASP-IV Program. Considering the economic aspect, nuclear power plant (NPP) is feasible in the future. From the geographical aspect Sumatra is prospecting for NPP site, especially the east coastal area due to the absence of hydro power potential and geothermal field. The use of petroleum as fuel in large scale power plants is not feasible. Beside causing high cost for electricity sector, it is also an important fuel for any other sectors such as transportation, electrification of isolated areas. Gas fuelled power plants is still feasible for next several decades in limited capacity. The study presents three scenarios, i.e. Low Scenario, Base Scenario and High Scenario applying discount rate of 8%, 10% and 12% respectively. Cost estimation for Sumatra System Expansion Planning is 57 465 million US$ on the Base Scenario - discount rate 8%, 59 349 million US$ on the Base Scenario - discount rate 10%, and 57 796 million US$ on the Base Scenario - discount rate 12%. The objective function is 15 172 US$ on the Base Scenario - discount rate 8%, 12 663 million US$ on the Base Scenario - discount rate 10%, and 11 017 million US$ on the Base Scenario - discount rate 12%. (author)

  18. Automated IMRT planning with regional optimization using planning scripts.

    Science.gov (United States)

    Xhaferllari, Ilma; Wong, Eugene; Bzdusek, Karl; Lock, Michael; Chen, Jeff

    2013-01-07

    Intensity-modulated radiation therapy (IMRT) has become a standard technique in radiation therapy for treating different types of cancers. Various class solutions have been developed for simple cases (e.g., localized prostate, whole breast) to generate IMRT plans efficiently. However, for more complex cases (e.g., head and neck, pelvic nodes), it can be time-consuming for a planner to generate optimized IMRT plans. To generate optimal plans in these more complex cases which generally have multiple target volumes and organs at risk, it is often required to have additional IMRT optimization structures such as dose limiting ring structures, adjust beam geometry, select inverse planning objectives and associated weights, and additional IMRT objectives to reduce cold and hot spots in the dose distribution. These parameters are generally manually adjusted with a repeated trial and error approach during the optimization process. To improve IMRT planning efficiency in these more complex cases, an iterative method that incorporates some of these adjustment processes automatically in a planning script is designed, implemented, and validated. In particular, regional optimization has been implemented in an iterative way to reduce various hot or cold spots during the optimization process that begins with defining and automatic segmentation of hot and cold spots, introducing new objectives and their relative weights into inverse planning, and turn this into an iterative process with termination criteria. The method has been applied to three clinical sites: prostate with pelvic nodes, head and neck, and anal canal cancers, and has shown to reduce IMRT planning time significantly for clinical applications with improved plan quality. The IMRT planning scripts have been used for more than 500 clinical cases.

  19. Using Optimization to Improve Test Planning

    Science.gov (United States)

    2017-09-01

    OPTIMIZATION TO IMPROVE TEST PLANNING by Arlene M. Payne September 2017 Thesis Advisor: Jeffrey E. Kline Second Reader: Oleg A. Yakimenko THIS... Project (0704-0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE September 2017 3. REPORT TYPE AND DATES COVERED Master’s...thesis 4. TITLE AND SUBTITLE USING OPTIMIZATION TO IMPROVE TEST PLANNING 5. FUNDING NUMBERS 6. AUTHOR(S) Arlene M. Payne 7. PERFORMING ORGANIZATION

  20. Expansion planning of brazilian electric sector: institutional changes, new policies and new instruments for planning

    International Nuclear Information System (INIS)

    Bajay, S.V.; Silva, W.A. da; Ricciulli, D.L.S.

    1990-01-01

    The Brazilian power supply industry has been in crisis for many years, particularly due to financial and institutional problems. There are many reasons for that, several of them from outside the industry. In this paper a diagnosis of the main elements of this crisis is worked out, in the context of the industry's expansion planning. Following, institutional changes, new policies and new instruments are proposed for this planning. The institutional setting, the demand studies, the demand side management, the supply optimisation, the rural electrification, the decentralized generation of electricity, the tariff structure, the ways of financing the industry, the technological advances, the social and environmental impacts and the integrated planning of the industry are discussed, together with the planning of the power supply industry interactions with the other energy supply industries and the rest of the economy. (author)

  1. Treatment planning optimization for linear accelerator radiosurgery

    International Nuclear Information System (INIS)

    Meeks, Sanford L.; Buatti, John M.; Bova, Francis J.; Friedman, William A.; Mendenhall, William M.

    1998-01-01

    Purpose: Linear accelerator radiosurgery uses multiple arcs delivered through circular collimators to produce a nominally spherical dose distribution. Production of dose distributions that conform to irregular lesions or conformally avoid critical neural structures requires a detailed understanding of the available treatment planning parameters. Methods and Materials: Treatment planning parameters that may be manipulated within a single isocenter to provide conformal avoidance and dose conformation to ellipsoidal lesions include differential arc weighting and gantry start/stop angles. More irregular lesions require the use of multiple isocenters. Iterative manipulation of treatment planning variables can be difficult and computationally expensive, especially if the effects of these manipulations are not well defined. Effects of treatment parameter manipulation are explained and illustrated. This is followed by description of the University of Florida Stereotactic Radiosurgery Treatment Planning Algorithm. This algorithm organizes the manipulations into a practical approach for radiosurgery treatment planning. Results: Iterative treatment planning parameters may be efficiently manipulated to achieve optimal treatment plans by following the University of Florida Treatment Planning Algorithm. The ability to produce conformal stereotactic treatment plans using the algorithm is demonstrated for a variety of clinical presentations. Conclusion: The standard dose distribution produced in linear accelerator radiosurgery is spherical, but manipulation of available treatment planning parameters may result in optimal dose conformation. The University of Florida Treatment Planning Algorithm organizes available treatment parameters to efficiently produce conformal radiosurgery treatment plans

  2. Computational optimization techniques applied to microgrids planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.

    2015-01-01

    Microgrids are expected to become part of the next electric power system evolution, not only in rural and remote areas but also in urban communities. Since microgrids are expected to coexist with traditional power grids (such as district heating does with traditional heating systems......), their planning process must be addressed to economic feasibility, as a long-term stability guarantee. Planning a microgrid is a complex process due to existing alternatives, goals, constraints and uncertainties. Usually planning goals conflict each other and, as a consequence, different optimization problems...... appear along the planning process. In this context, technical literature about optimization techniques applied to microgrid planning have been reviewed and the guidelines for innovative planning methodologies focused on economic feasibility can be defined. Finally, some trending techniques and new...

  3. Experiments Planning, Analysis, and Optimization

    CERN Document Server

    Wu, C F Jeff

    2011-01-01

    Praise for the First Edition: "If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library."-Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries-and sheds further light on existing ones-on the design and analysis of experiments and their applications in system optimization, robustness, and tre

  4. Optimization of importance factors in inverse planning

    International Nuclear Information System (INIS)

    Xing, L.

    1999-01-01

    Inverse treatment planning starts with a treatment objective and obtains the solution by optimizing an objective function. The clinical objectives are usually multifaceted and potentially incompatible with one another. A set of importance factors is often incorporated in the objective function to parametrize trade-off strategies and to prioritize the dose conformality in different anatomical structures. Whereas the general formalism remains the same, different sets of importance factors characterize plans of obviously different flavour and thus critically determine the final plan. Up to now, the determination of these parameters has been a 'guessing' game based on empirical knowledge because the final dose distribution depends on the parameters in a complex and implicit way. The influence of these parameters is not known until the plan optimization is completed. In order to compromise properly the conflicting requirements of the target and sensitive structures, the parameters are usually adjusted through a trial-and-error process. In this paper, a method to estimate these parameters computationally is proposed and an iterative computer algorithm is described to determine these parameters numerically. The treatment plan selection is done in two steps. First, a set of importance factors are chosen and the corresponding beam parameters (e.g. beam profiles) are optimized under the guidance of a quadratic objective function using an iterative algorithm reported earlier. The 'optimal' plan is then evaluated by an additional scoring function. The importance factors in the objective function are accordingly adjusted to improve the ranking of the plan. For every change in the importance factors, the beam parameters need to be re-optimized. This process continues in an iterative fashion until the scoring function is saturated. The algorithm was applied to two clinical cases and the results demonstrated that it has the potential to improve significantly the existing method of

  5. Multi-criteria Generation-Expansion Planning with Carbon dioxide emissions and Nuclear Safety considerations

    International Nuclear Information System (INIS)

    Lee, Hun Gyu; Kim, Young Chang

    2010-01-01

    A multiple criteria decision making (MCDM) method is developed to aid decision makers in Generation Expansion planning and management. Traditionally, the prime objective of an electric utility's generation-expansion planning has been to determine the minimum cost supply plans that meet expected demands over a planning horizon (typically 10 to 30 years). Today, however, the nature of decision environments has changed substantially. Increased policy attention is given to solve the multiple tradeoff function including environmental and social factors as well as economic one related to nuclear power expansion. In order to deal with this MCDM problem, the Analytic Hierarchy Process (AHP) Model is applied

  6. A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints

    International Nuclear Information System (INIS)

    Koltsaklis, Nikolaos E.; Georgiadis, Michael C.

    2015-01-01

    Highlights: • A short-term structured investment planning model has been developed. • Unit commitment problem is incorporated into the long-term planning horizon. • Inherent intermittency of renewables is modelled in a comprehensive way. • The impact of CO_2 emission pricing in long-term investment decisions is quantified. • The evolution of system’s marginal price is evaluated for all the planning horizon. - Abstract: This work presents a generic mixed integer linear programming (MILP) model that integrates the unit commitment problem (UCP), i.e., daily energy planning with the long-term generation expansion planning (GEP) framework. Typical daily constraints at an hourly level such as start-up and shut-down related decisions (start-up type, minimum up and down time, synchronization, soak and desynchronization time constraints), ramping limits, system reserve requirements are combined with representative yearly constraints such as power capacity additions, power generation bounds of each unit, peak reserve requirements, and energy policy issues (renewables penetration limits, CO_2 emissions cap and pricing). For modelling purposes, a representative day (24 h) of each month over a number of years has been employed in order to determine the optimal capacity additions, electricity market clearing prices, and daily operational planning of the studied power system. The model has been tested on an illustrative case study of the Greek power system. Our approach aims to provide useful insight into strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level by providing the optimal energy roadmap under real operating and design constraints.

  7. Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

    Science.gov (United States)

    Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

    2018-02-01

    Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

  8. Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion

    Directory of Open Access Journals (Sweden)

    Jing Qiu

    2017-07-01

    Full Text Available This paper presents a multi-objective transmission expansion planning (TEP framework. Rather than using the conventional deterministic reliability criterion, a risk component based on the probabilistic reliability criterion is incorporated into the TEP objectives. This risk component can capture the stochastic nature of power systems, such as load and wind power output variations, component availability, and incentive-based demand response (IBDR costs. Specifically, the formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to conduct risk analysis. Thus, a final expansion plan can be selected according to individual risk preferences. Moreover, the economic value of IBDR is modeled and integrated into the cost objective. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and risk are provided. The proposed approach is numerically verified on the Garver’s six-bus, IEEE 24-bus RTS and Polish 2383-bus systems. Case study results demonstrate that the proposed approach can effectively reduce cost and hedge risk in relation to increasing wind power integration.

  9. A capacity expansion planning model for integrated water desalination and power supply chain problem

    International Nuclear Information System (INIS)

    Saif, Y.; Almansoori, A.

    2016-01-01

    Highlights: • Water and power supply chain is considered by a discrete optimization model. • The model examines the capacity expansion and operation of the supply chain problem. • Renewable/alternative power technologies and carbon mitigation are considered. • A case study of Abu Dhabi in UAE is examined as an application of the model. - Abstract: Cogeneration of water and power in integrated cogeneration production plants is a common practice in the Middle East and North Africa (MENA) countries. There are several combinations of water desalination and power technologies which give significant adverse environmental impact. Renewable and alternative energy technologies have been recently proposed as alternative power production paths in the water and power sector. In this study, we examine the optimal capacity expansion of water and power infrastructure over an extended planning horizon. A generic mixed integer linear programming model is developed to assist in the decision making process on: (1) optimal installation of cogeneration expansion capacities; (2) optimal installation of renewable and alternative power plants; (3) optimal operation of the integrated water and power supply chain over large geographical areas. Furthermore, the model considers the installation of carbon capture methods in fossil-based power plants. A case study will be presented to illustrate the mathematical programming application for the Emirate of Abu Dhabi (AD) in the United Arab Emirates (UAE). The case study is solved reflecting different scenarios: base case scenario, integration of renewable and alternative technologies scenario, and CO_2 reduction targets scenario. The results show that increased carbon tax values up to 150 $/ton-CO_2 gives a maximum 3% cost increase for the supply chain net present value. The installation of carbon capture methods is not an economical solution due to its high operation energy requirements in the order of 370 kW h per ton of captured CO_2

  10. Banking towards development: Evidence from the Spanish banking expansion plan

    OpenAIRE

    Pere Arqué-Castells; Elisabet Viladecans-Marsal

    2013-01-01

    During the period 1965-1987 Spain was an emerging market in full transition from developing to developed status. During the same period the Spanish banking system underwent an unprecedented episode of expansion growing from 5,000 to over 30,000 bank branches. We examine whether the latter process partly caused the former by focusing on the relationship between branch expansion and entrepreneurship in the wholesale and retail trade industries. To address the non-random allocation of bank branc...

  11. A computational model for determining the minimal cost expansion alternatives in transmission systems planning; Um modelo computacional para determinacao de alternativas de expansao de custo minimo em planejamento de sistemas de transmissao

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, L M.V.G.; Pereira, M V.F. [Pontificia Univ. Catolica do Rio de Janeiro, RJ (Brazil); Nunes, A [ELETROBRAS, Rio de Janeiro, RJ (Brazil)

    1990-12-31

    A computational model for determining an economical transmission expansion plan, based in the decomposition techniques is presented. The algorithm was used in the Brazilian South System and was able to find an optimal solution, with a low computational resource. Some expansions of this methodology are been investigated: the probabilistic one and the expansion with financier restriction. (C.G.C.). 4 refs, 7 figs.

  12. Optimizing reserve expansion for disjunct populations of San Joaquin kit fox

    Science.gov (United States)

    Robert G. Haight; Brian Cypher; Patrick A. Kelly; Scott Phillips; Katherine Ralls; Hugh P. Possingham

    2004-01-01

    Expanding habitat protection is a common strategy for species conservation. We present a model to optimize the expansion of reserves for disjunct populations of an endangered species. The objective is to maximize the expected number of surviving populations subject to budget and habitat constraints. The model accounts for benefits of reserve expansion in terms of...

  13. System network planning expansion using mathematical programming, genetic algorithms and tabu search

    International Nuclear Information System (INIS)

    Sadegheih, A.; Drake, P.R.

    2008-01-01

    In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used

  14. Conventional treatment planning optimization using simulated annealing

    International Nuclear Information System (INIS)

    Morrill, S.M.; Langer, M.; Lane, R.G.

    1995-01-01

    Purpose: Simulated annealing (SA) allows for the implementation of realistic biological and clinical cost functions into treatment plan optimization. However, a drawback to the clinical implementation of SA optimization is that large numbers of beams appear in the final solution, some with insignificant weights, preventing the delivery of these optimized plans using conventional (limited to a few coplanar beams) radiation therapy. A preliminary study suggested two promising algorithms for restricting the number of beam weights. The purpose of this investigation was to compare these two algorithms using our current SA algorithm with the aim of producing a algorithm to allow clinically useful radiation therapy treatment planning optimization. Method: Our current SA algorithm, Variable Stepsize Generalized Simulated Annealing (VSGSA) was modified with two algorithms to restrict the number of beam weights in the final solution. The first algorithm selected combinations of a fixed number of beams from the complete solution space at each iterative step of the optimization process. The second reduced the allowed number of beams by a factor of two at periodic steps during the optimization process until only the specified number of beams remained. Results of optimization of beam weights and angles using these algorithms were compared using a standard cadre of abdominal cases. The solution space was defined as a set of 36 custom-shaped open and wedged-filtered fields at 10 deg. increments with a target constant target volume margin of 1.2 cm. For each case a clinically-accepted cost function, minimum tumor dose was maximized subject to a set of normal tissue binary dose-volume constraints. For this study, the optimized plan was restricted to four (4) fields suitable for delivery with conventional therapy equipment. Results: The table gives the mean value of the minimum target dose obtained for each algorithm averaged over 5 different runs and the comparable manual treatment

  15. A bi-level programming for multistage co-expansion planning of the integrated gas and electricity system

    DEFF Research Database (Denmark)

    Zeng, Qing; Zhang, Baohua; Fang, Jiakun

    2017-01-01

    as the generation capacities, while the lower-level is formulated as an optimal economic dispatch under the operational constraints given by the upper-level decision. To solve the bi-level multi-stage programming problem, a hybrid algorithm is proposed combining the modified binary particle swarm optimization (BPSO...... power systems. The system operation is optimized and embedded in the planning horizon. A bi-level multi-stage programming problem is formulated to minimize the investment cost plus the operational cost. The upper-level optimizes the expansion plan and determines the network topology as well......) and the interior point method (IPM). The BPSO is used for the upper-level sub-problem, and the IPM is adopted for the lower-level sub-problem. Numerical case studies have been carried out on the practical gas and electricity transmission network in western Denmark. Simulation results demonstrate the effectiveness...

  16. Optimization approaches for robot trajectory planning

    Directory of Open Access Journals (Sweden)

    Carlos Llopis-Albert

    2018-03-01

    Full Text Available The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof, the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.

  17. Helicopter trajectory planning using optimal control theory

    Science.gov (United States)

    Menon, P. K. A.; Cheng, V. H. L.; Kim, E.

    1988-01-01

    A methodology for optimal trajectory planning, useful in the nap-of-the-earth guidance of helicopters, is presented. This approach uses an adjoint-control transformation along with a one-dimensional search scheme for generating the optimal trajectories. In addition to being useful for helicopter nap-of-the-earth guidance, the trajectory planning solution is of interest in several other contexts, such as robotic vehicle guidance and terrain-following guidance for cruise missiles and aircraft. A distinguishing feature of the present research is that the terrain constraint and the threat envelopes are incorporated in the equations of motion. Second-order necessary conditions are examined.

  18. Optimized Planning Target Volume for Intact Cervical Cancer

    International Nuclear Information System (INIS)

    Khan, Alvin; Jensen, Lindsay G.; Sun Shuai; Song, William Y.; Yashar, Catheryn M.; Mundt, Arno J.; Zhang Fuquan; Jiang, Steve B.; Mell, Loren K.

    2012-01-01

    Purpose: To model interfraction clinical target volume (CTV) variation in patients with intact cervical cancer and design a planning target volume (PTV) that minimizes normal tissue dose while maximizing CTV coverage. Methods and Materials: We analyzed 50 patients undergoing external-beam radiotherapy for intact cervical cancer using daily online cone-beam computed tomography (CBCT). The CBCTs (n = 972) for each patient were rigidly registered to the planning CT. The CTV was delineated on the planning CT (CTV 0 ) and the set of CBCTs ({CTV 1 –CTV 25 }). Manual (n = 98) and automated (n = 668) landmarks were placed over the surface of CTV 0 with reference to defined anatomic structures. Normal vectors were extended from each landmark, and the minimum length required for a given probability of encompassing CTV 1 –CTV 25 was computed. The resulting expansions were used to generate an optimized PTV. Results: The mean (SD; range) normal vector length to ensure 95% coverage was 4.3 mm (2.7 mm; 1–16 mm). The uniform expansion required to ensure 95% probability of CTV coverage was 13 mm. An anisotropic margin of 20 mm anteriorly and posteriorly and 10 mm superiorly, inferiorly, and laterally also would have ensured a 95% probability of CTV coverage. The volume of the 95% optimized PTV (1470 cm 3 ) was significantly lower than both the anisotropic PTV (2220 cm 3 ) and the uniformly expanded PTV (2110 cm 3 ) (p 0 , 5–10 mm along the interfaces of CTV 0 with the bladder and rectum, and 10–14 mm along the anterior surface of CTV 0 at the level of the uterus. Conclusion: Optimizing PTV definition according to surface landmarking resulted in a high probability of CTV coverage with reduced PTV volumes. Our results provide data justifying planning margins to use in practice and clinical trials.

  19. Power system generation expansion planning using the maximum principle and analytical production cost model

    International Nuclear Information System (INIS)

    Lee, K.Y.; Park, Y.M.

    1991-01-01

    Historically, the electric utility demand in most countries has increased rapidly, with a doubling of approximately 10 years in the case of developing countries. In order to meet this growth in demand, the planners of expansion policies were concerned with obtaining expansion pans which dictate what new generation facilities to add and when to add them. This paper reports that, however, the practical planning problem is extremely difficult and complex, and required many hours of the planner's time even though the alternatives examined were extremely limited. In this connection, increased motivation for more sophisticated techniques of valuating utility expansion policies has been developed during the past decade. Among them, the long-range generation expansion planning is to select the most economical and reliable generation expansion plans in order to meet future power demand over a long period of time subject to a multitude of technical, economical, and social constraints

  20. When does treatment plan optimization require inverse planning?

    International Nuclear Information System (INIS)

    Sherouse, George W.

    1995-01-01

    Increasing maturity of image-based computer-aided design of three-dimensional conformal radiotherapy has recently sparked a great deal of work in the area of treatment plan optimization. Optimization of a conformal photon beam treatment plan is that exercise through which a set of intensity-modulated static beams or arcs is specified such that, when the plan is executed, 1) a region of homogeneous dose is produced in the patient with a shape which geometrically conforms (within a specified tolerance) to the three-dimensional shape of a designated target volume and 2) acceptably low incidental dose is delivered to non-target tissues. Interest in conformal radiotherapy arise from a fundamental assumption that there is significant value to be gained from aggressive customization of the treatment for each individual patient In our efforts to design optimal treatments, however, it is important to remember that, given the biological and economic realities of clinical radiotherapy, mathematical optimization of dose distribution metrics with respect to some minimal constraint set is not a necessary or even sufficient condition for design of a clinically optimal treatment. There is wide variation in the complexity of the clinical situations encountered in practice and there are a number of non-physical criteria to be considered in planning. There is also a complementary variety of computational and engineering means for achieving optimization. To date, the scientific dialogue regarding these techniques has concentrated on development of solutions to worst-case scenarios, largely in the absence of consideration of appropriate matching of solution complexity to problem complexity. It is the aim of this presentation to propose a provisional stratification of treatment planning problems, stratified by relative complexity, and to identify a corresponding stratification of necessary treatment planning techniques. It is asserted that the subset of clinical radiotherapy cases for

  1. Maintenance optimization plan for essential equipment reliability

    International Nuclear Information System (INIS)

    Steffen, D.H.

    1996-02-01

    The Maintenance Optimization Plan (MOP) for Essential Equipment Reliability will furnish Tank Waste Remediation System (TWRS) management with a pro-active, forward-thinking process for maintaining essential structures, systems, and components (ESSC) at the Hanford Site tank farms in their designed condition, and to ensure optimum ESSC availability and reliability

  2. Stochastic-based resource expansion planning for a grid-connected microgrid using interval linear programming

    International Nuclear Information System (INIS)

    Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar

    2016-01-01

    This paper represents a stochastic approach for long-term optimal resource expansion planning of a grid-connected microgrid (MG) containing different technologies as intermittent renewable energy resources, energy storage systems and thermal resources. Maximizing profit and reliability, along with minimizing investment and operation costs, are major objectives which have been considered in this model. Also, the impacts of intermittency and uncertainty in renewable energy resources were investigated. The interval linear programming (ILP) was applied for modelling inherent stochastic nature of the renewable energy resources. ILP presents some superiority in modelling of uncertainties in MG planning. The problem was formulated as a mixed-integer linear programming. It has been demonstrated previously that the benders decomposition (BD) served as an effective tool for solving such problems. BD divides the original problem into a master (investment) problem and operation and reliability subproblems. In this paper a multiperiod MG planning is presented, considering life time, maximum penetration limit of each technology, interest rate, capital recovery factor and investment fund. Real-time energy exchange with the utility is covered, with a consideration of variable tariffs at different load blocks. The presented approach can help MG planners to adopt best decision under various uncertainty levels based on their budgetary policies. - Highlights: • Considering uncertain nature of the renewable resources with applying ILP. • Considering the effect of intermittency of renewable in MG planning. • Multiobjective MG planning problem which covers cost, profit and reliability. • Multiperiod approach for MG planning considering life time and MPL of technologies. • Presenting real-time energy exchange with the utility considering variable tariffs.

  3. Temporal Optimization Planning for Fleet Repositioning

    DEFF Research Database (Denmark)

    Tierney, Kevin; Jensen, Rune Møller

    2011-01-01

    Fleet repositioning problems pose a high financial bur- den on shipping firms, but have received little attention in the literature, despite their high importance to the shipping industry. Fleet repositioning problems are characterized by chains of interacting activities, but state-of-the-art pla......Fleet repositioning problems pose a high financial bur- den on shipping firms, but have received little attention in the literature, despite their high importance to the shipping industry. Fleet repositioning problems are characterized by chains of interacting activities, but state......-of-the-art planning and scheduling techniques do not offer cost models that are rich enough to represent essential objectives of these problems. To this end, we introduce a novel framework called Temporal Optimization Planning (TOP). TOP uses partial order planning to build optimization models associated...

  4. Problems of heat sources modeling on stage of isolated power systems expansion planning

    International Nuclear Information System (INIS)

    Malenkov, A.V.; Reshetnikova, L.N.; Sergeev, Yu.A.

    1998-01-01

    It is necessary to use computer codes for evaluation of possible applications and role of nuclear district heating plants in the local self-balancing power and heating systems, which are to be located in the remote isolated and hardly accessible regions in the Far North of Russia. Key factors in determining system configurations and its performances are: (1) interdependency of electricity, heat and fuel supply; (2) long distance between energy consumer centres (from several tens up to some hundred kilometers); and (3) difficulty in export and import of the electricity, especially the fuel in and from neighbouring and remote regions. The problem to challenge is to work out an optimum expansion plan of the local electricity and heat supply system. The ENPEP (ENergy and Power Evaluation Program) software package, which was developed by IAEA together with the USA Argonne National Laboratory, was chosen for this purpose. The Chaun-Bilibino power system (CBPS), an isolated power system in far North-East region of Russia, was selected as the first case of the ENPEP study. ENPEP allows a complex approach in the system expansion optimization planning in the time frame of planning period of up to 30 years. The key ENPEP module, ELECTRIC, considers electricity as the only product. The cogeneration part (heat production) must be considered outside the ELECTRIC model and then the results to be transfer ed to ELECTRIC. The ENPEP study on the Chaun-Bilibino isolated power system has shown that the modelling of the heat supply sources in ENPEP is not a trivial problem. It is very important and difficult to correctly represent specific features of cogeneration process at the same time. (author)

  5. An investigation on the impacts of regulatory interventions on wind power expansion in generation planning

    International Nuclear Information System (INIS)

    Alishahi, Ehsan; Moghaddam, Mohsen P.; Sheikh-El-Eslami, Mohammad K.

    2011-01-01

    Large integration of intermittent wind generation in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. This paper presents a novel framework on the basis of a combination of stochastic dynamic programming (SDP) algorithm and game theory to study the impacts of different regulatory interventions to promote wind power investment in generation expansion planning. In this study, regulatory policies include Feed-in-Tariff (FIT) incentive, quota and tradable green certificate. The intermittent nature and uncertainties of wind power generation will cause the investors encounter risk in their investment decisions. To overcome this problem, a novel model has been derived to study the regulatory impacts on wind generation expansion planning. In our approach, the probabilistic nature of wind generation is modeled. The model can calculate optimal investment strategies, in which the wind power uncertainty is included. This framework is implemented on a test system to illustrate the working of the proposed approach. The result shows that FITs are the most effective policy to encourage the rapid and sustained deployment of wind power. FITs can significantly reduce the risks of investing in renewable energy technologies and thus create conditions conducive to rapid market growth. - Highlights: → The impacts of regulatory policies to promote wind power investment are investigated. → These policies include Feed-in-Tariff (FIT), quota and tradable green certificate. → Result shows that FIT is an effective policy to motivate the rapid growth of wind power. → In quota, customers are forced to provide the quota decided by regulators from wind.

  6. Incorporating a multi-criteria decision procedure into the combined dynamic programming/production simulation algorithm for generation expansion planning

    International Nuclear Information System (INIS)

    Yang, H.T.; Chen, S.L.

    1989-01-01

    A multi-objective optimization approach to generation expansion planning is presented. The approach is designed by adding a new multi-criteria decision (MCD) procedure to the conventional algorithm which combines dynamic programming with production simulation method. The MCD procedure can help decision makers weight the relative importance of multiple attributes associated with the decision alternatives, and find the near-best compromise solution efficiently at each optimization step of the conventional algorithm. Practical application of proposed approach to feasibility evaluation of the fourth nuclear power plant of Tawian is also presented, demonstrating the effectiveness and limitations of the approach

  7. Design of materials with extreme thermal expansion using a three-phase topology optimization method

    DEFF Research Database (Denmark)

    Sigmund, Ole; Torquato, S.

    1997-01-01

    We show how composites with extremal or unusual thermal expansion coefficients can be designed using a numerical topology optimization method. The composites are composed of two different material phases and void. The optimization method is illustrated by designing materials having maximum therma...

  8. Optimized planning methodologies of ASON implementation

    Science.gov (United States)

    Zhou, Michael M.; Tamil, Lakshman S.

    2005-02-01

    Advanced network planning concerns effective network-resource allocation for dynamic and open business environment. Planning methodologies of ASON implementation based on qualitative analysis and mathematical modeling are presented in this paper. The methodology includes method of rationalizing technology and architecture, building network and nodal models, and developing dynamic programming for multi-period deployment. The multi-layered nodal architecture proposed here can accommodate various nodal configurations for a multi-plane optical network and the network modeling presented here computes the required network elements for optimizing resource allocation.

  9. Optimal expansion of a drinking water infrastructure system with respect to carbon footprint, cost-effectiveness and water demand.

    Science.gov (United States)

    Chang, Ni-Bin; Qi, Cheng; Yang, Y Jeffrey

    2012-11-15

    Urban water infrastructure expansion requires careful long-term planning to reduce the risk from climate change during periods of both economic boom and recession. As part of the adaptation management strategies, capacity expansion in concert with other management alternatives responding to the population dynamics, ecological conservation, and water management policies should be systematically examined to balance the water supply and demand temporally and spatially with different scales. To mitigate the climate change impact, this practical implementation often requires a multiobjective decision analysis that introduces economic efficiencies and carbon-footprint matrices simultaneously. The optimal expansion strategies for a typical water infrastructure system in South Florida demonstrate the essence of the new philosophy. Within our case study, the multiobjective modeling framework uniquely features an integrated evaluation of transboundary surface and groundwater resources and quantitatively assesses the interdependencies among drinking water supply, wastewater reuse, and irrigation water permit transfer as the management options expand throughout varying dimensions. With the aid of a multistage planning methodology over the partitioned time horizon, such a systems analysis has resulted in a full-scale screening and sequencing of multiple competing objectives across a suite of management strategies. These strategies that prioritize 20 options provide a possible expansion schedule over the next 20 years that improve water infrastructure resilience and at low life-cycle costs. The proposed method is transformative to other applications of similar water infrastructure systems elsewhere in the world. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Optimal Patent Life in a Variety-Expansion Growth Model

    OpenAIRE

    Lin, Hwan C.

    2013-01-01

    This paper presents more channels through which the optimal patent life is determined in a R&D-based endogenous growth model that permits growth of new varieties of consumer goods over time. Its modeling features include an endogenous hazard rate facing incumbent monopolists, the prevalence of research congestion, and the aggregate welfare importance of product differentiation. As a result, a patent’s effective life is endogenized and less than its legal life. The model is calibrated to a glo...

  11. Transmission investment and expansion planning in a restructured electricity market

    International Nuclear Information System (INIS)

    Wu, F.F; Wen, F.S.; Zheng, F.L.

    2006-01-01

    Transmission planning in a restructured electricity market becomes increasingly complicated. To bridge the gap between economic and engineering considerations, this survey paper suggests a framework to clarify the interactions among various economic and engineering issues by reviewing recent theoretical and practical progress in transmission investment and transmission planning methodology. Thus, the paper makes economic literature more accessible to the engineering community and engineering literature more accessible to the economic community interested in the subject. (author)

  12. 94: Treatment plan optimization for conformal therapy

    International Nuclear Information System (INIS)

    Rosen, I.I.; Lane, R.G.

    1987-01-01

    Computer-controlled conformal radiation therapy techniques can deliver complex treatments utilizing large numbers of beams, gantry angles and beam shapes. Linear programming is well-suited for planning conformal treatments. Given a list of available treatment beams, linear programming calculates the relative weights of the beams such that the objective function is optimized and doses to constraint points are within the prescribed limits. 5 refs.; 3 figs

  13. Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization.

    Science.gov (United States)

    Kyroudi, Archonteia; Petersson, Kristoffer; Ghandour, Sarah; Pachoud, Marc; Matzinger, Oscar; Ozsahin, Mahmut; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

    2016-08-01

    Multi-criteria optimization provides decision makers with a range of clinical choices through Pareto plans that can be explored during real time navigation and then converted into deliverable plans. Our study shows that dosimetric differences can arise between the two steps, which could compromise the clinical choices made during navigation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  14. Practical method for generation expansion planning based on the dynamic programming. Dynamic programming ni motozuku dengen keikaku shuho

    Energy Technology Data Exchange (ETDEWEB)

    Tanabe, R.; Yasuda, K.; Yokoyama, R. (Tokyo Metropolitan Univ., Tokyo (Japan))

    1992-05-20

    To supply cheap, high-reliable and a planty of the electricity is an important task of the electric supply system because the requirement for the electricity is rapidly increased in Japan. In order to solve this problem, the authors of the paper are developing a most suitable practical method based on algorithm, according to which the generation expansion planning is divided into two problems: the optimal generation mix and the optimal generation construction process and the two problems are solved respectively. But there are some bad points in the method, for example, there are only approximative practical restriction of the capacity of single machine and the existing electric supply etc., because the optimal generation mix is determined on the basis of non-linear planning. So, in the present paper, the electric supply support system is practically constructed while proposing an unified generation expansion planning based on the dynamic programming that is possible to consider these restrictions strictly and the usefullness of the method is inspected. 12 refs., 7 figs., 5 tabs.

  15. The availability of the step optimization in Monaco planning system

    International Nuclear Information System (INIS)

    Kim, Dae Sup

    2014-01-01

    We present a method to reduce this gap and complete the treatment plan, to be made by the re-optimization is performed in the same conditions as the initial treatment plan different from Monaco treatment planning system. The optimization is carried in two steps when performing the inverse calculation for volumetric modulated radiation therapy or intensity modulated radiation therapy in Monaco treatment planning system. This study was the first plan with a complete optimization in two steps by performing all of the treatment plan, without changing the optimized condition from Step 1 to Step 2, a typical sequential optimization performed. At this time, the experiment was carried out with a pencil beam and Monte Carlo algorithm is applied In step 2. We compared initial plan and re-optimized plan with the same optimized conditions. And then evaluated the planning dose by measurement. When performing a re-optimization for the initial treatment plan, the second plan applied the step optimization. When the common optimization again carried out in the same conditions in the initial treatment plan was completed, the result is not the same. From a comparison of the treatment planning system, similar to the dose-volume the histogram showed a similar trend, but exhibit different values that do not satisfy the conditions best optimized dose, dose homogeneity and dose limits. Also showed more than 20% different in comparison dosimetry. If different dose algorithms, this measure is not the same out. The process of performing a number of trial and error, and you get to the ultimate goal of treatment planning optimization process. If carried out to optimize the completion of the initial trust only the treatment plan, we could be made of another treatment plan. The similar treatment plan could not satisfy to optimization results. When you perform re-optimization process, you will need to apply the step optimized conditions, making sure the dose distribution through the optimization

  16. Powering the people: India's capacity expansion plans

    Energy Technology Data Exchange (ETDEWEB)

    Patel, S.

    2009-05-15

    India has become a global business power even though hundreds of millions of its citizens still live in poverty. To sustain economic growth and lift its people out of poverty, India needs more and more reliable power. Details of government plans for achieving those goals demonstrate that pragmatism may be in shorter supply than ambition and political will. 1 ref., 12 figs., 1 tab.

  17. On distributive effects of optimal regulation for power grid expansion

    International Nuclear Information System (INIS)

    Herrera, Luis Ángel; Rosellón, Juan

    2014-01-01

    To date, the distributive implications of incentive regulation on electricity transmission networks have not been explicitly studied in the literature. More specifically, the parameters that a regulator might use to achieve distributive efficiency under price-cap regulation have not yet been identified. To discern these parameters is the motivation for the research presented in this paper. We study how different weight parameters affect the distributive characteristics of optimal price-cap incentive regulation for electricity transmission. We find that a regulator's use of ideal (Laspeyres) weights tends to be more beneficial for the Transco (consumers) than for consumers (the Transco). - Highlights: • Distributive implications of incentive regulation on transmission networks have not been studied in the literature. • The parameters that a regulator might use to achieve distributive efficiency have so far not been explicitly analyzed. • Analyze how different weights affect the distributive characteristics of price-cap regulation in electricity transmission. • Results: ideal (Laspeyres) weights tend to be more beneficial for the Transco (consumers) than for consumers (the Transco)

  18. Optimization of rotational radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Tulovsky, Vladimir; Ringor, Michael; Papiez, Lech

    1995-01-01

    Purpose: Rotational therapy treatment planning for rotationally symmetric geometry of tumor and healthy tissue provides an important example of testing various approaches to optimizing dose distributions for therapeutic x-ray irradiations. In this article, dose distribution optimization is formulated as a variational problem. This problem is solved analytically and numerically. Methods and Materials: The classical Lagrange method is used to derive equations and inequalities that give necessary conditions for minimizing the mean-square deviation between the ideal dose distribution and the achievable dose distribution. The solution of the resulting integral equation with Cauchy kernel is used to derive analytical formulas for the minimizing irradiation intensity function. Results: The solutions are evaluated numerically and the graphs of the minimizing intensity functions and the corresponding dose distributions are presented. Conclusions: The optimal solutions obtained using the mean-square criterion lead to significant underdosage in some areas of the tumor volume. Possible solutions to this shortcoming are investigated and medically more appropriate criteria for optimization are proposed for future investigations

  19. Leader-Follower Approach to Gas-Electricity Expansion Planning Problem

    DEFF Research Database (Denmark)

    Khaligh, Vahid; Oloomi Buygi, Majid; Anvari-Moghaddam, Amjad

    2018-01-01

    investment in capacity addition to the generation and transmission levels while considers the limitations on fuel consumption. On the other hand gas operator decides about investment in gas pipelines expansions considering the demanded gas by the electricity network. In this planning model for a joint gas......The main purpose of this paper is to develop a method for sequential gas and electricity networks expansion planning problem. A leader-follower approach performs the expansion planning of the joint gas and electricity networks. Electric system operator under adequacy incentive decides about......-electricity network, supply and demand are matched together while adequacy of fuel for gas consuming units is also guaranteed. To illustrate the effectiveness of the proposed method Khorasan province of Iran is considered as a case study which has a high penetration level of gas-fired power plants (GFPP). Also...

  20. WiMax network planning and optimization

    CERN Document Server

    Zhang, Yan

    2009-01-01

    This book offers a comprehensive explanation on how to dimension, plan, and optimize WiMAX networks. The first part of the text introduces WiMAX networks architecture, physical layer, standard, protocols, security mechanisms, and highly related radio access technologies. It covers system framework, topology, capacity, mobility management, handoff management, congestion control, medium access control (MAC), scheduling, Quality of Service (QoS), and WiMAX mesh networks and security. Enabling easy understanding of key concepts and technologies, the second part presents practical examples and illu

  1. Studying influence of two effective parameters on network losses in transmission expansion planning using DCGA

    International Nuclear Information System (INIS)

    Shayeghi, H.; Jalilzadeh, S.; Mahdavi, M.; Hadadian, H.

    2008-01-01

    Transmission network expansion planning (TNEP) is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. Its task is to minimize the network construction and operational cost, while meeting imposed technical, economic and reliability constraints. Up till now, various methods have been proposed for solution of the static transmission network expansion planning (STNEP) problem. But, in all of them, the effect of two important parameters i.e., inflation rate and load growth factor on network losses has not been investigated. Thus, in this paper, STNEP is being studied considering the effect of inflation rate and load growth factor on the network losses in a transmission network with different voltage levels using a decimal codification genetic algorithm (DCGA). The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the inflation rate and load growth factor have important effect on the network losses and subsequent network arrangement. In addition, considering the effect of two above-mentioned parameters (inflation rate and load growth factor) in expansion planning of transmission networks with various line voltage levels is caused that the total expansion cost of the network (expansion costs and the operational cost) is calculated more exactly and therefore the network satisfies the requirements of delivering electric power more safely and reliably to load centers

  2. Problems faced with the use of the WASP model in least cost and alternative electricity system expansion planning in Romania

    Energy Technology Data Exchange (ETDEWEB)

    Breazu, F [Institute of Power Studies and Design, Bucharest (Romania)

    1997-09-01

    Romanian experience with the use of IAEA planning methodologies was effectively initiated in 1989 with the launching of a Technical Cooperation project of the IAEA for the study of the energy demand and optimal expansion plans for the electricity generation system. The experience gathered during this project was crucial for the Romanian experts who conducted the studies. As a results, now Romania has a team of well trained experts in the use of the IAEA planning models. This paper describes the principal problems faced by Romanian planners in the use of these models with emphasis on the WASP package. Suggestions for future enhancements of the package are also part of this report. (author). 5 figs.

  3. Planning of the energy generation system expansion taking into account transmission lines; Planejamento da expansao do sistema de geracao considerando redes de transmissao

    Energy Technology Data Exchange (ETDEWEB)

    Lucio, Joao Carlos Martins

    1990-12-31

    This work presents the proposal of a methodology which, by exploring the interaction between generation and transmission systems expansion studies, aims for an Integrated Planning of Power Systems. It intends to emphasize the Integrated Planning importance so as to improve the utilization of the available resources in the electric sector and to reduce the expansion and operational costs. The work describes a procedure to consider explicitly the network for the determination of a generation system construction schedule. It considers that the transmission lines construction costs have a significant weight so that it can modify the initial generation expansion plan with the anticipation of some investments and the postponement of others, decreasing the global expansion costs. The generation and transmission systems expansion is made in an optimal way using a Graph Search Algorithm. Finally the best Integrated Plan is obtained from a final algorithm that generates a sequence of integrated plans from combination of generation and transmission algorithms. These plans are compared from a global cost point of view until a convergence criterion has been satisfied. (author) 18 refs., 5 figs., 28 tabs.

  4. Planning of the energy generation system expansion taking into account transmission lines; Planejamento da expansao do sistema de geracao considerando redes de transmissao

    Energy Technology Data Exchange (ETDEWEB)

    Lucio, Joao Carlos Martins

    1991-12-31

    This work presents the proposal of a methodology which, by exploring the interaction between generation and transmission systems expansion studies, aims for an Integrated Planning of Power Systems. It intends to emphasize the Integrated Planning importance so as to improve the utilization of the available resources in the electric sector and to reduce the expansion and operational costs. The work describes a procedure to consider explicitly the network for the determination of a generation system construction schedule. It considers that the transmission lines construction costs have a significant weight so that it can modify the initial generation expansion plan with the anticipation of some investments and the postponement of others, decreasing the global expansion costs. The generation and transmission systems expansion is made in an optimal way using a Graph Search Algorithm. Finally the best Integrated Plan is obtained from a final algorithm that generates a sequence of integrated plans from combination of generation and transmission algorithms. These plans are compared from a global cost point of view until a convergence criterion has been satisfied. (author) 18 refs., 5 figs., 28 tabs.

  5. A time consistent risk averse three-stage stochastic mixed integer optimization model for power generation capacity expansion

    International Nuclear Information System (INIS)

    Pisciella, P.; Vespucci, M.T.; Bertocchi, M.; Zigrino, S.

    2016-01-01

    We propose a multi-stage stochastic optimization model for the generation capacity expansion problem of a price-taker power producer. Uncertainties regarding the evolution of electricity prices and fuel costs play a major role in long term investment decisions, therefore the objective function represents a trade-off between expected profit and risk. The Conditional Value at Risk is the risk measure used and is defined by a nested formulation that guarantees time consistency in the multi-stage model. The proposed model allows one to determine a long term expansion plan which takes into account uncertainty, while the LCoE approach, currently used by decision makers, only allows one to determine which technology should be chosen for the next power plant to be built. A sensitivity analysis is performed with respect to the risk weighting factor and budget amount. - Highlights: • We propose a time consistent risk averse multi-stage model for capacity expansion. • We introduce a case study with uncertainty on electricity prices and fuel costs. • Increased budget moves the investment from gas towards renewables and then coal. • Increased risk aversion moves the investment from coal towards renewables. • Time inconsistency leads to a profit gap between planned and implemented policies.

  6. OPEC production: Capital limitations, environmental movements may interfere with expansion plans

    International Nuclear Information System (INIS)

    Ismail, I.A.H.

    1994-01-01

    Obtaining capital is a critical element in the production expansion plans of OPEC member countries. Another issue that may impact the plans is the environmental taxes that may reduce the call on OPEC oil by 5 million b/d in 2000 and about 16 million b/d in the year 2010. This concluding part of a two-part series discusses the expansion possibilities of non-Middle East OPEC members, OPEC's capital requirements, and environmental concerns. Non-Middle East OPEC includes Algeria, Gabon, Indonesia, Libya, Nigeria, and Venezuela

  7. Analysis of the security during power system expansion planning

    Directory of Open Access Journals (Sweden)

    Osak Alexey

    2017-01-01

    Full Text Available Increasing the intelligent level of the EPS control systems, caused by the implementation of Smart technologies, changes the structure and the properties of EPS and increases the importance of system reliability analysis. System reliability analysis includes two components – for the balance and for the regime. On the one hand, there is a large number of studies to assess the reliability of the power system, which examines various aspects and methods of solving this problem. On the other hand, in Russia there is no generally accepted methodology with clear criteria that could be used for feasibility studies of various technical solutions taking into consideration system reliability aspects. In practice, the security analysis is limited by the calculations of power flows, static and dynamic stability for a number of forecast periods for the normal and repair circuits considering the most severe disturbances. The existing approach allows defining the requirements and adjusting emergency control systems, but does not allow evaluating and comparing solutions for power grid constructions. The authors propose a new method for power system reliability evaluation, which is suitable for planning development and operation of power systems. The method includes a general description of the algorithm which allows to compare various development scenarios, as well as to assess the reliability level of their implementation. In particular, the method allows to determine where it is needed only the relay protection and emergency control system development, and where it is necessary grid, protection and control development and reconstruction.

  8. Effect of economic parameters on power generation expansion planning

    International Nuclear Information System (INIS)

    Sevilgen, Sueleyman Hakan; Hueseyin Erdem, Hasan; Cetin, Burhanettin; Volkan Akkaya, Ali; Dagdas, Ahmet

    2005-01-01

    The increasing consumption of electricity within time forces countries to build additional power plants. Because of technical and economic differences of the additional power plants, economic methodologies are used to determine the best technology for the additional capacity. The annual levelized cost method is used for this purpose, and the technology giving the minimum value for the additional load range is chosen. However, the economic parameters such as interest rate, construction escalation, fuel escalation, maintenance escalation and discount factor can affect the annual levelized cost considerably and change the economic range of the plants. Determining the values of the economical parameters in the future is very difficult, especially in developing countries. For this reason, the analysis of the changing rates of the mentioned values is of great importance for the planners of the additional capacity. In this study, the changing rates of the economic parameters that influence the annual levelized cost of the alternative power plant types are discussed. The alternative power plants considered for the electricity generation sector of Turkey and the economic parameters dominating each plant type are determined. It is clearly seen that the annual levelized cost for additional power plants varies with the economic parameters. The results show that the economic parameters variation has to be taken into consideration in electricity generation planning

  9. Optimal Investment Planning of Bulk Energy Storage Systems

    Directory of Open Access Journals (Sweden)

    Dina Khastieva

    2018-02-01

    Full Text Available Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.

  10. Optimization approaches to volumetric modulated arc therapy planning

    Energy Technology Data Exchange (ETDEWEB)

    Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu; Bortfeld, Thomas; Craft, David [Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States); Alber, Markus [Department of Medical Physics and Department of Radiation Oncology, Aarhus University Hospital, Aarhus C DK-8000 (Denmark); Bangert, Mark [Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg D-69120 (Germany); Bokrantz, Rasmus [RaySearch Laboratories, Stockholm SE-111 34 (Sweden); Chen, Danny [Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556 (United States); Li, Ruijiang; Xing, Lei [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Men, Chunhua [Department of Research, Elekta, Maryland Heights, Missouri 63043 (United States); Nill, Simeon [Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG (United Kingdom); Papp, Dávid [Department of Mathematics, North Carolina State University, Raleigh, North Carolina 27695 (United States); Romeijn, Edwin [H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Salari, Ehsan [Department of Industrial and Manufacturing Engineering, Wichita State University, Wichita, Kansas 67260 (United States)

    2015-03-15

    Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

  11. Evolutionary optimization technique for site layout planning

    KAUST Repository

    El Ansary, Ayman M.

    2014-02-01

    Solving the site layout planning problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to a favorite view). This paper introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique is based on genetic algorithm which explores the search space for possible solutions. This study considers two dimensional site planning problems. However, it can be extended to solve three dimensional cases. A case study is presented to demonstrate the efficiency of this technique in solving the site layout planning of simple residential dwellings. © 2013 Elsevier B.V. All rights reserved.

  12. Generation expansion planning of the electrical power system in West Java

    International Nuclear Information System (INIS)

    Nengah Sudja.

    1975-01-01

    A thorough study on the generation expansion planning of the electrical power system, covering mathematical and computerized calculations, and financial analysis on the daily load, the load duration, and the assumption of future load, supporting the idea for building nuclear power plants in Indonesia, is presented. (RUW)

  13. Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion (extended abstract)

    NARCIS (Netherlands)

    Spaan, M.T.J.; Oliehoek, F.A.; Amato, C.

    2011-01-01

    We advance the state of the art in optimal solving of decentralized partially observable Markov decision processes (Dec-POMDPs), which provide a formal model for multiagent planning under uncertainty.

  14. Aggressive plaque modification with rotational atherectomy and cutting balloon for optimal stent expansion in calcified lesions

    Science.gov (United States)

    Tang, Zhe; Bai, Jing; Su, Shao-Ping; Lee, Pui-Wai; Peng, Liang; Zhang, Tao; Sun, Ting; Nong, Jing-Guo; Li, Tian-De; Wang, Yu

    2016-01-01

    Objective To evaluate the factors affecting optimal stent expansion in calcified lesions treated by aggressive plaque modification with rotational atherectomy (RA) and a cutting balloon (CB). Methods From January 2014 to May 2015, 92 patients with moderate to severe coronary calcified lesions underwent rotational atherectomy and intravascular ultrasound imaging at Chinese PLA General Hospital (Beijing, China) were included in this study. They were divided into a rotational artherectomy combined with cutting balloon (RACB) group (46 patients treated with RA followed by CB angioplasty) and an RA group (46 patients treated with RA followed by plain balloon angioplasty). Another 40 patients with similar severity of their calcified lesions treated with plain old balloon angioplasty (POBA) were demographically matched to the other groups and defined as the POBA group. All patients received a drug-eluting stent after plaque preparation. Lumen diameter and lumen diameter stenosis (LDS) were measured by quantitative coronary angiography at baseline, after RA, after dilatation, and after stenting. Optimal stent expansion was defined as the final LDS < 10%. Results The initial and post-RA LDS values were similar among the three groups. However, after dilatation, the LDS significantly decreased in the RACB group (from 54.5% ± 8.9% to 36.1% ± 7.1%) but only moderately decreased (from 55.7% ± 7.8% to 46.9% ± 9.4%) in the RA group (time × group, P < 0.001). After stenting, there was a higher rate of optimal stent expansion in the RACB group (71.7% in the RACB group, 54.5% in the RA group, and 15% in the POBA group, P < 0.001), and the final LDS was significantly diminished in the RACB group compared to the other two groups (6.0% ± 2.3%, 10.8% ± 3.3%, 12.7% ± 2.1%, P < 0.001). Moreover, an LDS ≤ 40% after plaque preparation (OR = 2.994, 95% CI: 1.297–6.911) was associated with optimal stent expansion, which also had a positive correlation with the appearance of a

  15. Techno-economic and environmental analysis of power generation expansion plan of Ghana

    International Nuclear Information System (INIS)

    Awopone, Albert K.; Zobaa, Ahmed F.; Banuenumah, Walter

    2017-01-01

    This paper examines the current electrical generation expansion plan of Ghana and compares it with proposed expansion pathways with higher penetration of Renewable Energy Technologies. An adaptation of Schwartz's Scenario Methodology was used to develop the scenarios which were then analysed using the Long-range Alternatives Planning (LEAP) model. Each of the scenarios represents policy options for generation expansion in Ghana up to 2040. Energy, economic and environmental analysis of the three alternative scenarios compared to the base scenarios was undertaken. Sensitivity results show that, if the country were to follow the generation expansion path described in the renewable energy scenarios, it could reap economic benefits of 0.5–13.23% depending on the developments in fuel prices and renewable technology capital cost. The analysis further quantifies benefits to be derived from a reduction in Greenhouse gases of the scenarios. Policy implications for the generation system of Ghana based on the results are also discussed. - Highlights: • LEAP demand projection for Ghana from 2010 to 2014. • Develop scenarios using an adaptation of Schwartz’s scenario approach. • Develop LEAP model for generation scenario. • Each scenario represents possible generation expansion strategy. • High renewable energy systems penetration results in net economic and environmental benefits.

  16. Stability measures for rolling schedules with applications to capacity expansion planning, master production scheduling, and lot sizing

    OpenAIRE

    Kimms, Alf

    1996-01-01

    This contribution discusses the measurement of (in-)stability of finite horizon production planning when done on a rolling horizon basis. As examples we review strategic capacity expansion planning, tactical master production schedulng, and operational capacitated lot sizing.

  17. Planning method for integration and expansion of renewable energy sources with special attention to security supply in distribution system

    Energy Technology Data Exchange (ETDEWEB)

    Cerda-Arias, Jose Luis

    2012-07-01

    guide the expansion of the electrical system and coordinate solutions in order to obtain the maximal benefit for each new installation. The proposed method considers a temporary and spatial load forecasting model, the optimal distribution of the load into the grid, the proposal of new power generation projects and its branches, the planning of transmission and distribution systems and the classification of these proposed projects. The solution suggests a reduction of the active power losses due to the distribution of the load, the locations of new agents into the grid, and the interaction between transmission and the distribution system based on different tariff schemes. The usefulness of this method is highlighted by considering the influence of current variables which affect the behaviour of the load and the expansion of the power systems. The proposed method includes classical methodologies combined with exploratory development of other mathematical tools in the area of identification systems, the use of genetic algorithm, and the application of a branch and bound method, in the optimization methodology. The model is applied to a real system and shows the potential for its use in an analysis of the entry of new consumption devices, such as electric vehicles. The direct effect on each of the variables included in the analysis is distinguished mainly through the introduction of new components like energy efficiency in the load forecasting model, the effect of tariff scheme in the planning model, and the classification of projects in transmission and distribution systems.

  18. Three-dimensional photogrammetry for surgical planning of tissue expansion in hemifacial microsomia.

    Science.gov (United States)

    Jayaratne, Yasas S N; Lo, John; Zwahlen, Roger A; Cheung, Lim K

    2010-12-01

    We aim to illustrate the applications of 3-dimensional (3-D) photogrammetry for surgical planning and longitudinal assessment of the volumetric changes in hemifacial microsomia. A 3-D photogrammetric system was employed for planning soft tissue expansion and transplantation of a vascularized scapular flap for a patient with hemifacial microsomia. The facial deficiency was calculated by superimposing a mirror of the normal side on the preoperative image. Postsurgical volumetric changes were monitored by serial superimposition of 3-D images. A total of 31 cm(3) of tissue expansion was achieved within a period of 4 weeks. A scapular free flap measuring 8 cm × 5 cm was transplanted to augment the facial deficiency. Postsurgical shrinkage of the flap was observed mainly in the first 3 months and it was minimal thereafter. 3-D photogrammetry can be used as a noninvasive objective tool for assessing facial deformity, planning, and postoperative follow-up of surgical correction of facial asymmetry.

  19. Planning the expansion of electrical transmission networks with evolutionary programming; Planeacion de la expansion de redes de transmision electrica con programacion evolucionaria

    Energy Technology Data Exchange (ETDEWEB)

    Ceciliano Meza, Jose Luis

    1997-12-31

    In this work it is presented for the first time in the literature the solution of the problem of the planning the expansion of an electrical transmission network (PERTE) with the use of the Evolutionary Programming. The evolutionary programming is a stochastic method of optimization with similar characteristics to the generic algorithms, but different. During the development of this work it is shown what each one of these two heuristic methods of optimization consist of. Additionally, the main characteristics of other two heuristic methods known in the literature are described (Tabu Searching and Simulated Annealing). These two methods together with the genetic algorithms and decomposition of Benders have also been used to solve the problem of planning PERTE. The operation of the proposed algorithm of evolutionary programming was tested in two networks of electrical transmission. The first case of test is a system which is known in the literature. The second case is a representative system of the electrical transmission network of Central America. The results obtained improve all the results shown when applying different heuristic methods of optimization (genetic algorithms, simulated annealing and Tabu searching) to solve the same problem. [Espanol] En este trabajo se presenta por primera vez en la literatura, la solucion del problema de la planeacion de expansion de una red de transmision electrica (PERTE) con el uso de la Programacion Evolucionaria. La programacion evolucionaria es un metodo estocastico de optimizacion con caracteristicas similares a los algoritmos geneticos, pero diferente. Durante el desarrollo de este trabajo se muestra en que consiste cada uno de estos dos metodos heuristicos de optimizacion. Ademas, se describen las caracteristicas principales de otros dos metodos heuristicos conocidos en la literatura (busqueda Tabu y Recorrido Simulado). Estos dos metodos juntos con los algoritmos geneticos y descomposicion de Benders tambien han sido

  20. [Ecological suitability assessment and optimization of urban land expansion space in Guiyang City].

    Science.gov (United States)

    Qiu, Cong-hao; Li, Yang-bing; Feng, Yuan-song

    2015-09-01

    Based on the case study of Guiyang City, the minimum cumulative resistance model integrating construction land source, ecological rigid constraints and ecological function type resistance factor, was built by use of cost-distance analysis of urban spatial expansion resistance value through ArcGIS 9.3 software in this paper. Then, the ecological resistance of city spatial expansion of Guiyang from 2010 was simulated dynamically and the ecological suitability classification of city spatial expansion was assessed. According to the conflict between the newly increased city construction land in 2014 and its ecological suitability, the unreasonable city land spatial allocation was discussed also. The results showed that the ecological suitability zonation and the city expansion in the study area were basically consistent during 2010-2014, but the conflict between the new city construction and its land ecological suitability was more serious. The ecological conflict area accounted for 58.2% of the new city construction sites, 35.4% of which happened in the ecological control area, 13.9% in the limited development area and 8.9% in the prohibition development area. The intensification of ecological land use conflict would impair the ecological service function and ecological safety, so this paper put forward the city spatial expansion optimal path to preserve the ecological land and improve the construction land space pattern of Guiyang City so as to ensure its ecological safety.

  1. Impact of equipment failures and wind correlation on generation expansion planning

    DEFF Research Database (Denmark)

    Pineda, S.; Morales, J.M.; Ding, Y.

    2014-01-01

    the generating company (GENCO) and the system operator. The upper-level problem maximizes the GENCO's expected profit, while the lower-level problem simulates an hourly market-clearing procedure, through which LMPs are determined. The uncertainty pertaining to failures and wind power correlation is characterized......Generation expansion planning has become a complex problem within a deregulated electricity market environment due to all the uncertainties affecting the profitability of a given investment. Current expansion models usually overlook some of these uncertainties in order to reduce the computational...

  2. Optimizing the Long-Term Capacity Expansion and Protection of Iraqi Oil Infrastructure

    Science.gov (United States)

    2005-09-01

    remotely using only a computer and a high-speed internet connection. I only wish that the Navy as a whole were as receptive to telecommuting as you...INTRODUCTION Formula for success: Rise early, work hard , strike oil. Jean Paul Getty (1892-1976), American Industrialist and Founder of the Getty...In truth , Iraq has neglected its lifeblood industry for far too long and requires a capital expansion and security plan - as well as the financial

  3. Wien Automatic System Planning (WASP) Package. A computer code for power generating system expansion planning. Version WASP-III Plus. User's manual. Volume 1: Chapters 1-11

    International Nuclear Information System (INIS)

    1995-01-01

    As a continuation of its effort to provide comprehensive and impartial guidance to Member States facing the need for introducing nuclear power, the IAEA has completed a new version of the Wien Automatic System Planning (WASP) Package for carrying out power generation expansion planning studies. WASP was originally developed in 1972 in the USA to meet the IAEA's needs to analyze the economic competitiveness of nuclear power in comparison to other generation expansion alternatives for supplying the future electricity requirements of a country or region. The model was first used by the IAEA to conduct global studies (Market Survey for Nuclear Power Plants in Developing Countries, 1972-1973) and to carry out Nuclear Power Planning Studies for several Member States. The WASP system developed into a very comprehensive planning tool for electric power system expansion analysis. Following these developments, the so-called WASP-Ill version was produced in 1979. This version introduced important improvements to the system, namely in the treatment of hydroelectric power plants. The WASP-III version has been continually updated and maintained in order to incorporate needed enhancements. In 1981, the Model for Analysis of Energy Demand (MAED) was developed in order to allow the determination of electricity demand, consistent with the overall requirements for final energy, and thus, to provide a more adequate forecast of electricity needs to be considered in the WASP study. MAED and WASP have been used by the Agency for the conduct of Energy and Nuclear Power Planning Studies for interested Member States. More recently, the VALORAGUA model was completed in 1992 as a means for helping in the preparation of the hydro plant characteristics to be input in the WASP study and to verify that the WASP overall optimized expansion plan takes also into account an optimization of the use of water for electricity generation. The combined application of VALORAGUA and WASP permits the

  4. Wien Automatic System Planning (WASP) Package. A computer code for power generating system expansion planning. Version WASP-IV. User's manual

    International Nuclear Information System (INIS)

    2001-01-01

    generated by each plant and the user specified characteristics of fuels used. Expanded dimensions for handling up to 90 types of plants and a larger number of configurations (up to 500 per year and 5000 for the study period). The present manual allows us to support the use of the WASP-IV version and to illustrate the capabilities of the model. This manual contains 13 chapters. Chapter 1 gives a summary description of WASP-IV Computer Code and its Modules and file system. Chapter 2 explains the hardware requirement and the installation of the package. The sequence of the execution of WASP-IV is also briefly introduced in this chapter. Chapters 3 to 9 explains, in detail, how to execute each of the module of WASP-IV package, the organisation of input files and output from the run of the model. Special attention was paid to the description of the linkage of modules. Chapter 10 specially guides the users on how to effectively search for an optimal solution. Chapter 11 describes the execution of sensitivity analyses that can be (recommend to be) performed with WASP-IV. To ease the debugging during the running of the software, Chapter 12 provides technical details of the new features incorporated in this version. Chapter 13 provides a list of error and warning messages produced for each module of WASP. The reader of this manual is assumed to have experience in the field of power generation expansion planning and to be familiar with all concepts related to such type of analysis, therefore these aspects are not treated in this manual. Additional information on power generation expansion planning can be found in the IAEA publication 'Expansion Planning for Electrical Generating Systems, A Guidebook', Technical Reports Series No. 241 (1984) or User's Manual of WASP-IV Plus, Computer Manual Series No. 8, (1995)

  5. Decision analysis in the expansion planning of the Mexican Electrical System

    International Nuclear Information System (INIS)

    Toupiol, S.; Martin del Campo M, C.; Ortega C, R.

    2007-01-01

    In the last years, the planning of the National Interconnected System has been guided mainly to technologies of combined cycle, contributing to the establishment of a generation system little diversified and clerk of the readiness and volatility of the prices of natural gas. On the other hand, the electric system continues expanding without to consider the emissions of gases coming from the electric generation and the significant participation of the renewable and nuclear technologies in the production of electricity like decisive parameters for the long term planning, for what the developed plans are economically attractive but they don't contribute to the respect of the environment, to the sustainable development, neither to the diversification. With base to the above-mentioned intended in this work to develop viable outlines for the long term expansion of the National Interconnected System (period 2005-2024), appealing to the pattern of uni nodal planning that uses the Federal Commission of Electricity at the moment (CFE) that is to say the pattern WASP given by the International Atomic Energy Agency. This way, you fixed as objective to propose two expansion alternatives to the reference plan developed by the CFE in 2005 for the period 2005-2024, with the purpose of not only looking for the good plan of these three plans in terms of the total cost of generation, but also in terms of the risk associated to the price of natural gas, the emissions of dioxide of sulfur and nitrogen oxides generated by the plants of the system and the diversity of the generation park. To compare the three developed plans, you applies an analysis of decision of multiple approaches based on the approach of Savage. Finally, starting from this analysis, he/she intended to determine if the plan of minimum cost represents the long term better option or if it suits but to expand the system being based on a plan that represents the best commitment cost-risk-emission-diversity. (Author)

  6. Integrated multiperiod power generation and transmission expansion planning with sustainability aspects in a stochastic environment

    International Nuclear Information System (INIS)

    Seddighi, Amir Hossein; Ahmadi-Javid, Amir

    2015-01-01

    This paper presents a multistage stochastic programming model to address sustainable power generation and transmission expansion planning. The model incorporates uncertainties about future electricity demand, fuel prices, greenhouse gas emissions, as well as possible disruptions to which the power system is subject. A number of sustainability regulations and policies are considered to establish a framework for the social responsibility of the power system. The proposed model is applied to a real-world case, and several sensitivity analyses are carried out to provide managerial insights into different aspects of the model. The results emphasize the important role played by sustainability policies on the configuration of the power grid. - Highlights: • This paper considers integrated power generation and transmission expansion planning. • Sustainability aspects are incorporated into a multiperiod stochastic setting. • A stochastic mathematical programming model is developed to address the problem. • The model is applied to a real-world case and numerical studies are carried out

  7. Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Yun-Hao Li

    2015-12-01

    Full Text Available This paper presents a flexible transmission network expansion planning (TNEP approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

  8. A comparative assessment of the long term electricity expansion plans in Mexico by using the position vector of minimum regret analysis

    International Nuclear Information System (INIS)

    Martindelcampo, C.; Gonzalezbello, C. R.

    2012-01-01

    A comparative assessment of alternative expansion plans for the Mexican electricity generating system was made by applying the Position Vector of Minimum Regret Analysis (PVMRA) as a decision analysis tool. Four expansion plans were ranked according to the following decision criteria: The cost which calculates the cumulated cost of electricity generation during the time period studied. The external cost which brings into play the costs associated with the impact on health and the environment. The risk which takes into account the economic impact associated with incremental fuel prices from the baseline scenario to the high scenario. The diversity which evaluates the generation park diversity in terms of the Shannon-Weaner Index. The foreign-capital fraction in investment using foreign inputs. The carbon-free fraction which evaluates electricity generation that contributes to climate change policies. The cost of severe-accidents which is the sum of full chain damage costs and external costs of severe accidents with at least 10 injured. Optimizations were made by internalizing the external cost into the objective function of the WASP-IV model, the cost of externalise of the operation and maintenance cost, and these expansions were compared with those that did not. Special attention was paid to studying the convenience of including nuclear power in the electricity generation mix. Furthermore, better electricity expansion plans, with lower internal and external costs, were also found when the optimization had included externalise

  9. AC transmission network expansion planning considering circuits repowering and location of capacitors

    OpenAIRE

    Jaime A. López-López; Diego A. Tejada-Arango; Jesús M. López-Lezama

    2016-01-01

    This paper deals with the Transmission Network Expansion Planning (TNEP) problem. The TNEP consists of finding a set of new circuits on a power system, which is needed to attend a future demand. In its classical version, the TNEP only considers as solution candidates the addition of new lines and transformers. The main contribution of this paper consists in the inclusion of nonconventional solution candidates, namely the repowering of existing circuits and the location of capacitor banks. To ...

  10. Technical papers presented at the 4. symposium of specialists in electric operational and expansion planning. v. 2; Artigos tecnicos apresentados no 4. simposio de especialistas em planejamento da operacao e expansao eletrica. v. 2

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    This symposium about electric operational and expansion planning presents several articles that approaches issues such as, monitoring the power system stability, electrical load modelling, reliability in power systems, optimization in power systems, integrated resources planning in power systems, reactive control through static compensators, power flow analysis, system modelling, etc

  11. Experimental performance analysis and optimization of a direct expansion solar-assisted heat pump water heater

    International Nuclear Information System (INIS)

    Li, Y.W.; Wang, R.Z.; Wu, J.Y.; Xu, Y.X.

    2007-01-01

    In this study, a direct expansion solar-assisted heat pump water heater (DX-SAHPWH) with rated input power 750 W was tested and analyzed. Through experimental research in spring and thermodynamics analysis about the system performance, some suggestions for the system optimization are proposed. Then, a small-type DX-SAHPWH with rated input power 400 W was built, tested and analyzed. Through exergy analysis for each component of DX-SAHPWH (A) and (B), it can be seen that the highest exergy loss occurs in the compressor and collector/evaporator, followed by the condenser and expansion valve, respectively. Furthermore, some methods are suggested to improve the performance of each component, especially the collector/evaporator. A methodology for the design optimization of the collector/evaporator was introduced and applied. In order to maintain a proper matching between the heat pumping capacity of the compressor and the evaporative capacity of the collector/evaporator under widely varying ambient conditions, the electronic expansion valve and variable frequency compressor are suggested to be utilized for the DX-SAHPWH

  12. Impact of Operating Rules on Planning Capacity Expansion of Urban Water Supply Systems

    Science.gov (United States)

    de Neufville, R.; Galelli, S.; Tian, X.

    2017-12-01

    This study addresses the impact of operating rules on capacity planning of urban water supply systems. The continuous growth of metropolitan areas represents a major challenge for water utilities, which often rely on industrial water supply (e.g., desalination, reclaimed water) to complement natural resources (e.g., reservoirs). These additional sources increase the reliability of supply, equipping operators with additional means to hedge against droughts. How do their rules for using industrial water supply impact the performance of water supply system? How might it affect long-term plans for capacity expansion? Possibly significantly, as demonstrated by the analysis of the operations and planning of a water supply system inspired by Singapore. Our analysis explores the system dynamics under multiple inflow and management scenarios to understand the extent to which alternative operating rules for the use of industrial water supply affect system performance. Results first show that these operating rules can have significant impact on the variability in system performance (e.g., reliability, energy use) comparable to that of hydro-climatological conditions. Further analyses of several capacity expansion exercises—based on our original hydrological and management scenarios—show that operating rules significantly affect the timing and magnitude of critical decisions, such as the construction of new desalination plants. These results have two implications: Capacity expansion analysis should consider the effect of a priori uncertainty about operating rules; and operators should consider how their flexibility in operating rules can affect their perceived need for capacity.

  13. A multiple objective mixed integer linear programming model for power generation expansion planning

    Energy Technology Data Exchange (ETDEWEB)

    Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)

    2004-03-01

    Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)

  14. Modeling and solving a large-scale generation expansion planning problem under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Shan; Ryan, Sarah M. [Iowa State University, Department of Industrial and Manufacturing Systems Engineering, Ames (United States); Watson, Jean-Paul [Sandia National Laboratories, Discrete Math and Complex Systems Department, Albuquerque (United States); Woodruff, David L. [University of California Davis, Graduate School of Management, Davis (United States)

    2011-11-15

    We formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices. Our model is expressed as a two-stage stochastic mixed-integer program, which we use to compute solutions independently minimizing the expected cost and the Conditional Value-at-Risk; i.e., the risk of significantly larger-than-expected operational costs. We introduce stochastic process models to capture demand and fuel price uncertainty, which are in turn used to generate trees that accurately represent the uncertainty space. Using a realistic problem instance based on the Midwest US, we explore two fundamental, unexplored issues that arise when solving any stochastic generation expansion model. First, we introduce and discuss the use of an algorithm for computing confidence intervals on obtained solution costs, to account for the fact that a finite sample of scenarios was used to obtain a particular solution. Second, we analyze the nature of solutions obtained under different parameterizations of this method, to assess whether the recommended solutions themselves are invariant to changes in costs. The issues are critical for decision makers who seek truly robust recommendations for generation expansion planning. (orig.)

  15. Vector-model-supported approach in prostate plan optimization

    International Nuclear Information System (INIS)

    Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Lehman, Margot; Pryor, David; Chan, Lawrence Wing Chi

    2017-01-01

    Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

  16. Vector-model-supported approach in prostate plan optimization

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Lehman, Margot; Pryor, David [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)

    2017-07-01

    Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration

  17. Development of the computer model by using LINGO for Electric System Expansion Planning

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Man Ki; Kim, Seung Su [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1994-05-01

    The main purpose of this study is to develop the electric system expansion planning model based on linear programming method and to describe how to use the model. The algorithm of linear programming is provided by LINGO. The decision variables are electric generation capacity per period and electricity generated by fuel types per year. Integer program is implemented in the model in order to consider indivisibility of electric capacities. The model also allows the constraint of CO{sub 2} to be considered in the planning. (Author) 4 refs.,.

  18. Point charges optimally placed to represent the multipole expansion of charge distributions.

    Directory of Open Access Journals (Sweden)

    Ramu Anandakrishnan

    Full Text Available We propose an approach for approximating electrostatic charge distributions with a small number of point charges to optimally represent the original charge distribution. By construction, the proposed optimal point charge approximation (OPCA retains many of the useful properties of point multipole expansion, including the same far-field asymptotic behavior of the approximate potential. A general framework for numerically computing OPCA, for any given number of approximating charges, is described. We then derive a 2-charge practical point charge approximation, PPCA, which approximates the 2-charge OPCA via closed form analytical expressions, and test the PPCA on a set of charge distributions relevant to biomolecular modeling. We measure the accuracy of the new approximations as the RMS error in the electrostatic potential relative to that produced by the original charge distribution, at a distance 2x the extent of the charge distribution--the mid-field. The error for the 2-charge PPCA is found to be on average 23% smaller than that of optimally placed point dipole approximation, and comparable to that of the point quadrupole approximation. The standard deviation in RMS error for the 2-charge PPCA is 53% lower than that of the optimal point dipole approximation, and comparable to that of the point quadrupole approximation. We also calculate the 3-charge OPCA for representing the gas phase quantum mechanical charge distribution of a water molecule. The electrostatic potential calculated by the 3-charge OPCA for water, in the mid-field (2.8 Å from the oxygen atom, is on average 33.3% more accurate than the potential due to the point multipole expansion up to the octupole order. Compared to a 3 point charge approximation in which the charges are placed on the atom centers, the 3-charge OPCA is seven times more accurate, by RMS error. The maximum error at the oxygen-Na distance (2.23 Å is half that of the point multipole expansion up to the octupole

  19. Planning model for the expansion of the electrical generation system with risk demarcation criteria; Modelo para la planificacion de la expansion del sistema electrico de generacion con criterios de acotamiento de riesgo

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez Galicia, Julio Alberto; Nieva Gomez, Rolando [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)

    2009-07-01

    The general characteristics of a planning model for the electrical generation system expansion with risk demarcation criteria, as well as the main results of a representative study case of the Mexican Electrical System is presented. The model is based on a methodology of multiannual optimization for the generation expansion plans determination. In this context, every expansion plan defines the technology type to be installed, as well as the installation year, unit size and its location within a regional electric network. For this purpose, the model considers an interregional representation of the system identifying the necessary reinforcements to the capacity of the interregional connections. It also incorporates a Demarcation of Risk module that considers the uncertainty of the future scenarios of fuels prices to generate a set of expansion plans, among which includes the following: a) For every future of the fuel prices: the plan that diminishes the present value of the total cost (investment plus production). b) The plan that diminishes the economic risk derived from the uncertainty in the future of the fuel prices. c) A subgroup of expansion plans that are located in the efficient borders of decision, under the context of three criteria of interest: the economic risk, the investment cost of and the total cost in the future considered of greater relevance. [Spanish] Se presentan las caracteristicas generales de un modelo de planificacion de la expansion del sistema electrico de generacion con criterios de acotamiento de riesgo, asi como los principales resultados de un caso de estudio representativo del Sistema Electrico Mexicano. El modelo se basa en una metodologia de optimacion multi-anual para la determinacion de planes de expansion de la generacion. En este contexto, cada plan de expansion define el tipo de tecnologia que debera instalarse, asi como el ano de instalacion, el tamano de la unidad y su localizacion dentro de una red electrica regional. Para

  20. Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China

    Directory of Open Access Journals (Sweden)

    Peng Wang

    2018-06-01

    Full Text Available Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%. Different key performance indicators (KPI differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML produces the optimal power development path, as it provides the lowest discounted cost.

  1. Optimal Expansion of a Drinking Water Infrastructure System with Respect to Carbon Footprint, Cost Effectiveness and Water Demand

    Science.gov (United States)

    Urban water infrastructure requires careful long-term expansion planning to reduce the risk from climate change during both the periods of economic boom and recession. As part of the adaptation management strategies, capacity expansion in concert with other management alternativ...

  2. Wien Automatic System Planning (WASP) Package. A computer code for power generating system expansion planning. Version WASP-III Plus. User's manual. Volume 1: Chapters 1-11

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-09-01

    As a continuation of its effort to provide comprehensive and impartial guidance to Member States facing the need for introducing nuclear power, the IAEA has completed a new version of the Wien Automatic System Planning (WASP) Package for carrying out power generation expansion planning studies. WASP was originally developed in 1972 in the USA to meet the IAEA's needs to analyze the economic competitiveness of nuclear power in comparison to other generation expansion alternatives for supplying the future electricity requirements of a country or region. The model was first used by the IAEA to conduct global studies (Market Survey for Nuclear Power Plants in Developing Countries, 1972-1973) and to carry out Nuclear Power Planning Studies for several Member States. The WASP system developed into a very comprehensive planning tool for electric power system expansion analysis. Following these developments, the so-called WASP-Ill version was produced in 1979. This version introduced important improvements to the system, namely in the treatment of hydroelectric power plants. The WASP-III version has been continually updated and maintained in order to incorporate needed enhancements. In 1981, the Model for Analysis of Energy Demand (MAED) was developed in order to allow the determination of electricity demand, consistent with the overall requirements for final energy, and thus, to provide a more adequate forecast of electricity needs to be considered in the WASP study. MAED and WASP have been used by the Agency for the conduct of Energy and Nuclear Power Planning Studies for interested Member States. More recently, the VALORAGUA model was completed in 1992 as a means for helping in the preparation of the hydro plant characteristics to be input in the WASP study and to verify that the WASP overall optimized expansion plan takes also into account an optimization of the use of water for electricity generation. The combined application of VALORAGUA and WASP permits the

  3. Optimism and Planning for Future Care Needs among Older Adults

    Science.gov (United States)

    Sörensen, Silvia; Hirsch, Jameson K.; Lyness, Jeffrey M.

    2015-01-01

    Aging is associated with an increase in need for assistance. Preparation for future care (PFC) is related to improved coping ability as well as better mental and physical health outcomes among older adults. We examined the association of optimism with components of PFC among older adults. We also explored race differences in the relationship between optimism and PFC. In Study 1, multiple regression showed that optimism was positively related to concrete planning. In Study 2, optimism was related to gathering information. An exploratory analysis combining the samples yielded a race interaction: For Whites higher optimism, but for Blacks lower optimism was associated with more planning. High optimism may be a barrier to future planning in certain social and cultural contexts. PMID:26045699

  4. Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning.

    Science.gov (United States)

    Engberg, Lovisa; Forsgren, Anders; Eriksson, Kjell; Hårdemark, Björn

    2017-06-01

    To formulate convex planning objectives of treatment plan multicriteria optimization with explicit relationships to the dose-volume histogram (DVH) statistics used in plan quality evaluation. Conventional planning objectives are designed to minimize the violation of DVH statistics thresholds using penalty functions. Although successful in guiding the DVH curve towards these thresholds, conventional planning objectives offer limited control of the individual points on the DVH curve (doses-at-volume) used to evaluate plan quality. In this study, we abandon the usual penalty-function framework and propose planning objectives that more closely relate to DVH statistics. The proposed planning objectives are based on mean-tail-dose, resulting in convex optimization. We also demonstrate how to adapt a standard optimization method to the proposed formulation in order to obtain a substantial reduction in computational cost. We investigated the potential of the proposed planning objectives as tools for optimizing DVH statistics through juxtaposition with the conventional planning objectives on two patient cases. Sets of treatment plans with differently balanced planning objectives were generated using either the proposed or the conventional approach. Dominance in the sense of better distributed doses-at-volume was observed in plans optimized within the proposed framework. The initial computational study indicates that the DVH statistics are better optimized and more efficiently balanced using the proposed planning objectives than using the conventional approach. © 2017 American Association of Physicists in Medicine.

  5. Frontiers in planning optimization for lung SBRT.

    Science.gov (United States)

    Giglioli, Francesca Romana; Clemente, Stefania; Esposito, Marco; Fiandra, Christian; Marino, Carmelo; Russo, Serenella; Strigari, Lidia; Villaggi, Elena; Stasi, Michele; Mancosu, Pietro

    2017-12-01

    Emerging data are showing the safety and the efficacy of Stereotactic Body Radiation therapy (SBRT) in lung cancer management. In this context, the very high doses delivered to the Planning Target Volume, make the planning phase essential for achieving high dose levels conformed to the shape of the target in order to have a good prognosis for tumor control and to avoid an overdose in relevant healthy adjacent tissue. In this non-systematic review we analyzed the technological and the physics aspects of SBRT planning for lung cancer. In particular, the aims of the study were: (i) to evaluate prescription strategies (homogeneous or inhomogeneous), (ii) to outline possible geometrical solutions by comparing the dosimetric results (iii) to describe the technological possibilities for a safe and effective treatment, (iv) to present the issues concerning radiobiological planning and the automation of the planning process. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  6. Automatic interactive optimization for volumetric modulated arc therapy planning

    International Nuclear Information System (INIS)

    Tol, Jim P; Dahele, Max; Peltola, Jarkko; Nord, Janne; Slotman, Ben J; Verbakel, Wilko FAR

    2015-01-01

    Intensity modulated radiotherapy treatment planning for sites with many different organs-at-risk (OAR) is complex and labor-intensive, making it hard to obtain consistent plan quality. With the aim of addressing this, we developed a program (automatic interactive optimizer, AIO) designed to automate the manual interactive process for the Eclipse treatment planning system. We describe AIO and present initial evaluation data. Our current institutional volumetric modulated arc therapy (RapidArc) planning approach for head and neck tumors places 3-4 adjustable OAR optimization objectives along the dose-volume histogram (DVH) curve that is displayed in the optimization window. AIO scans this window and uses color-coding to differentiate between the DVH-lines, allowing it to automatically adjust the location of the optimization objectives frequently and in a more consistent fashion. We compared RapidArc AIO plans (using 9 optimization objectives per OAR) with the clinical plans of 10 patients, and evaluated optimal AIO settings. AIO consistency was tested by replanning a single patient 5 times. Average V95&V107 of the boost planning target volume (PTV) and V95 of the elective PTV differed by ≤0.5%, while average elective PTV V107 improved by 1.5%. Averaged over all patients, AIO reduced mean doses to individual salivary structures by 0.9-1.6Gy and provided mean dose reductions of 5.6Gy and 3.9Gy to the composite swallowing structures and oral cavity, respectively. Re-running AIO five times, resulted in the aforementioned parameters differing by less than 3%. Using the same planning strategy as manually optimized head and neck plans, AIO can automate the interactive Eclipse treatment planning process and deliver dosimetric improvements over existing clinical plans

  7. Evaluation of enrollee satisfaction with Iowa's Dental Wellness Plan for the Medicaid expansion population.

    Science.gov (United States)

    Reynolds, Julie C; McKernan, Susan C; Sukalski, Jennifer M C; Damiano, Peter C

    2018-12-01

    Dental coverage for Iowa's Medicaid expansion population is provided through the Dental Wellness Plan (DWP), implemented in May 2014. The plan targets healthy behavior incentives via an earned benefits structure, whereby additional services are covered if enrollees return every 6-12 months for routine dental visits. This study examines enrollee satisfaction with the DWP. We surveyed a random sample of DWP enrollees 1 year after program implementation about their experiences. Survey items covered dental plan satisfaction, self-rated measures of health, and knowledge and attitudes toward the earned benefits approach. Dental plan satisfaction was rated as low by 38 percent of respondents (n = 416), moderate by 25 percent (n = 276), and high by 37 percent (n = 402). A majority of respondents (66 percent) did not know about the earned benefits structure. Regression analysis indicated that respondents most likely to have low plan satisfaction were those who felt it was difficult to earn benefits (OR 3.66, P < 0.001) and those who were unable to find (OR 3.17, P < 0.001), or did not try to find (OR 3.51, P < 0.001), a regular dentist in the plan. Satisfaction with a new model of dental insurance was influenced by whether enrollees had a regular source of care and their perceived ability to return for regular checkups in order to earn covered benefits. © 2017 American Association of Public Health Dentistry.

  8. UMTS network planning, optimization, and inter-operation with GSM

    CERN Document Server

    Rahnema, Moe

    2008-01-01

    UMTS Network Planning, Optimization, and Inter-Operation with GSM is an accessible, one-stop reference to help engineers effectively reduce the time and costs involved in UMTS deployment and optimization. Rahnema includes detailed coverage from both a theoretical and practical perspective on the planning and optimization aspects of UMTS, and a number of other new techniques to help operators get the most out of their networks. Provides an end-to-end perspective, from network design to optimizationIncorporates the hands-on experiences of numerous researchersSingle

  9. Data Center Optimization Initiative Strategic Plans

    Data.gov (United States)

    Social Security Administration — On August 1, 2016, the Office of Management and Budget issued memorandum M-16-19, establishing the Data Center Optimization Initiative (DCOI). The DCOI, as described...

  10. Optimal production planning for PCB assembly

    CERN Document Server

    Ho, William

    2006-01-01

    Focuses on the optimization of the Printed circuit board (PCB) assembly lines' efficiency. This book integrates the component sequencing and the feeder arrangement problems together for the pick-and-place machine and the chip shooter machines.

  11. Evolutionary optimization technique for site layout planning

    KAUST Repository

    El Ansary, Ayman M.; Shalaby, Mohamed

    2014-01-01

    of design requirements. The developed technique is based on genetic algorithm which explores the search space for possible solutions. This study considers two dimensional site planning problems. However, it can be extended to solve three dimensional cases. A

  12. PLN's experience with the WASP-III model in generation expansion planning for the Java system

    International Nuclear Information System (INIS)

    Sudja, N.; Afiff, A.; Simarmata, B.

    1988-01-01

    The State Electric Power Corporation of Indonesia (PLN) was one of the first recipients of the WASP computer model, and since 1976 has been using the model (first the version WASP-II, and later the WASP-III version) for carrying out generation expansion planning studies for the country, and particularly, for the Java power system. This paper discusses PLN's experience with WASP-III and comments on some problems and constraints encountered, particularly: the time-fixed forced outage rate (FOR) assumed for generating units, simulation of the hydro system and computation time. The paper concludes with some suggestions about future enhancements to WASP-III. (author). 3 figs, 11 tabs

  13. Generation Expansion Planning with Large Amounts of Wind Power via Decision-Dependent Stochastic Programming

    DEFF Research Database (Denmark)

    Zhan, Yiduo; Zheng, Qipeng; Wang, Jianhui

    2016-01-01

    , the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming......Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined...

  14. On the role of modeling parameters in IMRT plan optimization

    International Nuclear Information System (INIS)

    Krause, Michael; Scherrer, Alexander; Thieke, Christian

    2008-01-01

    The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

  15. The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations

    Energy Technology Data Exchange (ETDEWEB)

    Kirby, Brendan J [ORNL

    2006-07-01

    Investigating the role of demand resources in regional transmission planning has provided mixed results. On one hand there are only a few projects where demand response has been used as an explicit alternative to transmission enhancement. On the other hand there is a fair amount of demand response in the form of energy efficiency, peak reduction, emergency load shedding, and (recently) demand providing ancillary services. All of this demand response reduces the need for transmission enhancements. Demand response capability is typically (but not always) factored into transmission planning as a reduction in the load which must be served. In that sense demand response is utilized as an alternative to transmission expansion. Much more demand response is used (involuntarily) as load shedding under extreme conditions to prevent cascading blackouts. The amount of additional transmission and generation that would be required to provide the current level of reliability if load shedding were not available is difficult to imagine and would be impractical to build. In a very real sense demand response solutions are equitably treated in every region - when proposed, demand response projects are evaluated against existing reliability and economic criteria. The regional councils, RTOs, and ISOs identify needs. Others propose transmission, generation, or responsive load based solutions. Few demand response projects get included in transmission enhancement plans because few are proposed. But this is only part of the story. Several factors are responsible for the current very low use of demand response as a transmission enhancement alternative. First, while the generation, transmission, and load business sectors each deal with essentially the same amount of electric power, generation and transmission companies are explicitly in the electric power business but electricity is not the primary business focus of most loads. This changes the institutional focus of each sector. Second

  16. Normalisation: ROI optimal treatment planning - SNDH pattern

    International Nuclear Information System (INIS)

    Shilvat, D.V.; Bhandari, Virendra; Tamane, Chandrashekhar; Pangam, Suresh

    2001-01-01

    Dose precision maximally to the target / ROI (Region of Interest), taking care of tolerance dose of normal tissue is the aim of ideal treatment planning. This goal is achieved with advanced modalities such as, micro MLC, simulator and 3-dimensional treatment planning system. But SNDH PATTERN uses minimum available resources as, ALCYON II Telecobalt unit, CT Scan, MULTIDATA 2-dimensional treatment planning system to their maximum utility and reaches to the required precision, same as that with advance modalities. Among the number of parameters used, 'NORMALISATION TO THE ROI' will achieve the aim of the treatment planning effectively. This is dealing with an example of canal of esophagus modified treatment planning based on SNDH pattern. Results are attractive and self explanatory. By implementing SNDH pattern, the QUALITY INDEX of treatment plan will reach to greater than 90%, with substantial reduction in dose to the vital organs. Aim is to utilize the minimum available resources efficiently to achieve highest possible precision for delivering homogenous dose to ROI while taking care of tolerance dose to vital organs

  17. Optimizing perioperative decision making: improved information for clinical workflow planning.

    Science.gov (United States)

    Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

    2012-01-01

    Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

  18. Multi-objective optimization of inverse planning for accurate radiotherapy

    International Nuclear Information System (INIS)

    Cao Ruifen; Pei Xi; Cheng Mengyun; Li Gui; Hu Liqin; Wu Yican; Jing Jia; Li Guoli

    2011-01-01

    The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set. (authors)

  19. AC transmission network expansion planning considering circuits repowering and location of capacitors

    Directory of Open Access Journals (Sweden)

    Jaime A. López-López

    2016-07-01

    Full Text Available This paper deals with the Transmission Network Expansion Planning (TNEP problem. The TNEP consists of finding a set of new circuits on a power system, which is needed to attend a future demand. In its classical version, the TNEP only considers as solution candidates the addition of new lines and transformers. The main contribution of this paper consists in the inclusion of nonconventional solution candidates, namely the repowering of existing circuits and the location of capacitor banks. To take into account these last ones an AC model of the transmission network is considered. The solution of the proposed model is carried out using a Hybrid Genetic Algorithm. Results are compared and validated with previous works in the technical literature. The test systems used are the Garver system and IEEE 24 bus system. The results obtained in both systems showed that the inclusion of the non-conventional candidates, proposed in this paper, allows to reduce the cost of network expansion. This fact may be useful as an indicator for the system planner to consider new possibilities in the expansion studies.

  20. Integrating robust timetabling in line plan optimization for railway systems

    DEFF Research Database (Denmark)

    Burggraeve, Sofie; Bull, Simon Henry; Vansteenwegen, Pieter

    2017-01-01

    We propose a heuristic algorithm to build a railway line plan from scratch that minimizes passenger travel time and operator cost and for which a feasible and robust timetable exists. A line planning module and a timetabling module work iteratively and interactively. The line planning module......, but is constrained by limited shunt capacity. While the operator and passenger cost remain close to those of the initially and (for these costs) optimally built line plan, the timetable corresponding to the finally developed robust line plan significantly improves the minimum buffer time, and thus the robustness...... creates an initial line plan. The timetabling module evaluates the line plan and identifies a critical line based on minimum buffer times between train pairs. The line planning module proposes a new line plan in which the time length of the critical line is modified in order to provide more flexibility...

  1. Improved Planning Time and Plan Quality Through Multicriteria Optimization for Intensity-Modulated Radiotherapy

    International Nuclear Information System (INIS)

    Craft, David L.; Hong, Theodore S.; Shih, Helen A.; Bortfeld, Thomas R.

    2012-01-01

    Purpose: To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT). Methods and Materials: Ten IMRT patients (5 with glioblastoma and 5 with locally advanced pancreatic cancers) were logged during the standard treatment planning procedure currently in use at Massachusetts General Hospital (MGH). Planning durations and other relevant planning information were recorded. In parallel, the patients were planned using an MCO planning system, and similar planning time data were collected. The patients were treated with the standard plan, but each MCO plan was also approved by the physicians. Plans were then blindly reviewed 3 weeks after planning by the treating physician. Results: In all cases, the treatment planning time was vastly shorter for the MCO planning (average MCO treatment planning time was 12 min; average standard planning time was 135 min). The physician involvement time in the planning process increased from an average of 4.8 min for the standard process to 8.6 min for the MCO process. In all cases, the MCO plan was blindly identified as the superior plan. Conclusions: This provides the first concrete evidence that MCO-based planning is superior in terms of both planning efficiency and dose distribution quality compared with the current trial and error–based IMRT planning approach.

  2. APPLICATION OF RESTART COVARIANCE MATRIX ADAPTATION EVOLUTION STRATEGY (RCMA-ES TO GENERATION EXPANSION PLANNING PROBLEM

    Directory of Open Access Journals (Sweden)

    K. Karthikeyan

    2012-10-01

    Full Text Available This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMA-ES to the Generation Expansion Planning (GEP problem. RCMA-ES is a class of continuous Evolutionary Algorithm (EA derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP. The GEP problem of a synthetic test systems for 6-year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.

  3. NSGA-II algorithm for multi-objective generation expansion planning problem

    Energy Technology Data Exchange (ETDEWEB)

    Murugan, P.; Kannan, S. [Electronics and Communication Engineering Department, Arulmigu Kalasalingam College of Engineering, Krishnankoil 626190, Tamilnadu (India); Baskar, S. [Electrical Engineering Department, Thiagarajar College of Engineering, Madurai 625015, Tamilnadu (India)

    2009-04-15

    This paper presents an application of Elitist Non-dominated Sorting Genetic Algorithm version II (NSGA-II), to multi-objective generation expansion planning (GEP) problem. The GEP problem is considered as a two-objective problem. The first objective is the minimization of investment cost and the second objective is the minimization of outage cost (or maximization of reliability). To improve the performance of NSGA-II, two modifications are proposed. One modification is incorporation of Virtual Mapping Procedure (VMP), and the other is introduction of controlled elitism in NSGA-II. A synthetic test system having 5 types of candidate units is considered here for GEP for a 6-year planning horizon. The effectiveness of the proposed modifications is illustrated in detail. (author)

  4. Using heuristic search for optimizing maintenance plans

    International Nuclear Information System (INIS)

    Mutanen, Teemu

    2012-01-01

    This work addresses the maintenance action selection process. Maintenance personnel need to evaluate maintenance actions and costs to keep the machines in working condition. Group of actions are evaluated together as maintenance plans. The maintenance plans as output provide information to the user about which actions to take if any and what future actions should be prepared for. The heuristic search method is implemented as part of general use toolbox for analysis of measurements from movable work machines. Impacts from machine's usage restrictions and maintenance activities are analysed. The results show that once put on a temporal perspective, the prioritized order of the actions is different and provide additional information to the user.

  5. The use of many-body expansions and geometry optimizations in fragment-based methods.

    Science.gov (United States)

    Fedorov, Dmitri G; Asada, Naoya; Nakanishi, Isao; Kitaura, Kazuo

    2014-09-16

    many-body expansion in a formally two-body series, as exemplified in the development of the fragment molecular orbital (FMO) method. Fragment-based methods have been very successful in delivering the properties of fragments, as well as the fragment interactions, providing insights into complex chemical processes in large molecular systems. We briefly review geometry optimizations performed with fragment-based methods and present an efficient geometry optimization method based on the combination of FMO with molecular mechanics (MM), applied to the complex of a subunit of protein kinase 2 (CK2) with a ligand. FMO results are discussed in comparison with experimental and MM-optimized structures.

  6. Optimization of energy planning strategies in municipalities

    DEFF Research Database (Denmark)

    Petersen, Jens-Phillip

    approach, suffers from insufficient information, tools and resources. Municipalities are often unable to take on a steering role in community energy planning. To overcome these barriers and guide municipalities in the pre-project phase, a decision-support methodology, based on community energy profiles...

  7. Software for CATV Design and Frequency Plan Optimization

    OpenAIRE

    Hala, O.

    2007-01-01

    The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

  8. Allogeneic cell therapy bioprocess economics and optimization: single-use cell expansion technologies.

    Science.gov (United States)

    Simaria, Ana S; Hassan, Sally; Varadaraju, Hemanthram; Rowley, Jon; Warren, Kim; Vanek, Philip; Farid, Suzanne S

    2014-01-01

    For allogeneic cell therapies to reach their therapeutic potential, challenges related to achieving scalable and robust manufacturing processes will need to be addressed. A particular challenge is producing lot-sizes capable of meeting commercial demands of up to 10(9) cells/dose for large patient numbers due to the current limitations of expansion technologies. This article describes the application of a decisional tool to identify the most cost-effective expansion technologies for different scales of production as well as current gaps in the technology capabilities for allogeneic cell therapy manufacture. The tool integrates bioprocess economics with optimization to assess the economic competitiveness of planar and microcarrier-based cell expansion technologies. Visualization methods were used to identify the production scales where planar technologies will cease to be cost-effective and where microcarrier-based bioreactors become the only option. The tool outputs also predict that for the industry to be sustainable for high demand scenarios, significant increases will likely be needed in the performance capabilities of microcarrier-based systems. These data are presented using a technology S-curve as well as windows of operation to identify the combination of cell productivities and scale of single-use bioreactors required to meet future lot sizes. The modeling insights can be used to identify where future R&D investment should be focused to improve the performance of the most promising technologies so that they become a robust and scalable option that enables the cell therapy industry reach commercially relevant lot sizes. The tool outputs can facilitate decision-making very early on in development and be used to predict, and better manage, the risk of process changes needed as products proceed through the development pathway. © 2013 Wiley Periodicals, Inc.

  9. Optimization in underground mine planning - developments and opportunities

    OpenAIRE

    Musingwini, C.

    2016-01-01

    The application of mining-specific and generic optimization techniques in the mining industry is deeply rooted in the discipline of operations research (OR). OR has its origins in the British Royal Air Force and Army around the early 1930s. Its development continued during and after World War II. The application of OR techniques to optimization in the mining industry started to emerge in the early 1960s. Since then, optimization techniques have been applied to solve widely different mine plan...

  10. Decision analysis in the expansion planning of the Mexican Electrical System; Analisis de decision en la planificacion de la expansion del Sistema Electrico Mexicano

    Energy Technology Data Exchange (ETDEWEB)

    Toupiol, S.; Martin del Campo M, C.; Ortega C, R. [Departamento de Sistemas Energeticos, Facultad de Ingenieria UNAM, Circuito Exterior s/n, Ciudad Universitaria, 04510 Mexico D.F. (Mexico)]. e-mail: stoupiol@yahoo.fr

    2007-07-01

    In the last years, the planning of the National Interconnected System has been guided mainly to technologies of combined cycle, contributing to the establishment of a generation system little diversified and clerk of the readiness and volatility of the prices of natural gas. On the other hand, the electric system continues expanding without to consider the emissions of gases coming from the electric generation and the significant participation of the renewable and nuclear technologies in the production of electricity like decisive parameters for the long term planning, for what the developed plans are economically attractive but they don't contribute to the respect of the environment, to the sustainable development, neither to the diversification. With base to the above-mentioned intended in this work to develop viable outlines for the long term expansion of the National Interconnected System (period 2005-2024), appealing to the pattern of uni nodal planning that uses the Federal Commission of Electricity at the moment (CFE) that is to say the pattern WASP given by the International Atomic Energy Agency. This way, you fixed as objective to propose two expansion alternatives to the reference plan developed by the CFE in 2005 for the period 2005-2024, with the purpose of not only looking for the good plan of these three plans in terms of the total cost of generation, but also in terms of the risk associated to the price of natural gas, the emissions of dioxide of sulfur and nitrogen oxides generated by the plants of the system and the diversity of the generation park. To compare the three developed plans, you applies an analysis of decision of multiple approaches based on the approach of Savage. Finally, starting from this analysis, he/she intended to determine if the plan of minimum cost represents the long term better option or if it suits but to expand the system being based on a plan that represents the best commitment cost-risk-emission-diversity. (Author)

  11. Identification of optimal strategies for energy management systems planning under multiple uncertainties

    International Nuclear Information System (INIS)

    Cai, Y.P.; Huang, G.H.; Yang, Z.F.; Tan, Q.

    2009-01-01

    Management of energy resources is crucial for many regions throughout the world. Many economic, environmental and political factors are having significant effects on energy management practices, leading to a variety of uncertainties in relevant decision making. The objective of this research is to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a fuzzy-random interval programming (FRIP) model. The method is based on an integration of the existing interval linear programming (ILP), superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP). Such a FRIP model allows multiple uncertainties presented as interval values, possibilistic and probabilistic distributions, as well as their combinations within a general optimization framework. It can also be used for facilitating capacity-expansion planning of energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term energy management planning for a region with three cities. Useful solutions for the planning of energy management systems were generated. Interval solutions associated with different risk levels of constraint violation were obtained. They could be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks could be successfully tackled, i.e., higher costs will increase system stability, while a desire for lower

  12. Optimal motion planning using navigation measure

    Science.gov (United States)

    Vaidya, Umesh

    2018-05-01

    We introduce navigation measure as a new tool to solve the motion planning problem in the presence of static obstacles. Existence of navigation measure guarantees collision-free convergence at the final destination set beginning with almost every initial condition with respect to the Lebesgue measure. Navigation measure can be viewed as a dual to the navigation function. While the navigation function has its minimum at the final destination set and peaks at the obstacle set, navigation measure takes the maximum value at the destination set and is zero at the obstacle set. A linear programming formalism is proposed for the construction of navigation measure. Set-oriented numerical methods are utilised to obtain finite dimensional approximation of this navigation measure. Application of the proposed navigation measure-based theoretical and computational framework is demonstrated for a motion planning problem in a complex fluid flow.

  13. Multi area and multistage expansion-planning of electricity supply with sustainable energy development criteria: a multi objective model

    Energy Technology Data Exchange (ETDEWEB)

    Unsihuay-Vila, Clodomiro; Marangon-Lima, J.W.; Souza, A.C Zambroni de [Universidade Federal de Itajuba (UNIFEI), MG (Brazil)], emails: clodomirounsihuayvila @gmail.com, marangon@unifei.edu.br, zambroni@unifei.edu.br; Perez-Arriaga, I.J. [Universidad Pontificia Comillas, Madrid (Spain)], email: ipa@mit.edu

    2010-07-01

    A novel multi objective, multi area and multistage model to long-term expansion-planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a multi-regional multi-objective and 'bottom-up' energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewable, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The MESEDES model considers three objectives belonging to sustainable energy development criteria such as: a) the minimization of investments and operation costs of : power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; b) minimization of Life Cycle Greenhouse Gas Emissions (LC GHG); c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM - Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework. (author)

  14. A multistage framework for reliability-based distribution expansion planning considering distributed generations by a self-adaptive global-based harmony search algorithm

    International Nuclear Information System (INIS)

    Shivaie, Mojtaba; Ameli, Mohammad T.; Sepasian, Mohammad S.; Weinsier, Philip D.; Vahidinasab, Vahid

    2015-01-01

    In this paper, the authors present a new multistage framework for reliability-based Distribution Expansion Planning (DEP) in which expansion options are a reinforcement and/or installation of substations, feeders, and Distributed Generations (DGs). The proposed framework takes into account not only costs associated with investment, maintenance, and operation, but also expected customer interruption cost in the optimization as four problem objectives. At the same time, operational restrictions, Kirchhoff's laws, radial structure limitation, voltage limits, and capital expenditure budget restriction are considered as problem constraints. The proposed model is a non-convex optimization problem having a non-linear, mixed-integer nature. Hence, a hybrid Self-adaptive Global-based Harmony Search Algorithm (SGHSA) and Optimal Power Flow (OPF) were used and followed by a fuzzy satisfying method in order to obtain the final optimal solution. The SGHSA is a recently developed optimization algorithm which imitates the music improvisation process. In this process, the harmonists improvise their instrument pitches, searching for the perfect state of harmony. The planning methodology was demonstrated on the 27-node, 13.8-kV test system in order to demonstrate the feasibility and capability of the proposed model. Simulation results illustrated the sufficiency and profitableness of the newly developed framework, when compared with other methods. - Highlights: • A new multistage framework is presented for reliability-based DEP problem. • In this paper, DGs are considered as an expansion option to increase the flexibility of the proposed model. • In this paper, effective factors of DEP problem are incorporated as a multi-objective model. • In this paper, three new algorithms HSA, IHSA and SGHSA are proposed. • Results obtained by the proposed SGHSA algorithm are better than others

  15. PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning

    International Nuclear Information System (INIS)

    Fiege, Jason; McCurdy, Boyd; Potrebko, Peter; Champion, Heather; Cull, Andrew

    2011-01-01

    Purpose: In radiation therapy treatment planning, the clinical objectives of uniform high dose to the planning target volume (PTV) and low dose to the organs-at-risk (OARs) are invariably in conflict, often requiring compromises to be made between them when selecting the best treatment plan for a particular patient. In this work, the authors introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a multiobjective optimization tool to solve for beam angles and fluence patterns in intensity-modulated radiation therapy (IMRT) treatment planning. Methods: pareto is built around a powerful multiobjective genetic algorithm (GA), which allows us to treat the problem of IMRT treatment plan optimization as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. We have employed a simple parameterized beam fluence representation with a realistic dose calculation approach, incorporating patient scatter effects, to demonstrate feasibility of the proposed approach on two phantoms. The first phantom is a simple cylindrical phantom containing a target surrounded by three OARs, while the second phantom is more complex and represents a paraspinal patient. Results: pareto results in a large database of Pareto nondominated solutions that represent the necessary trade-offs between objectives. The solution quality was examined for several PTV and OAR fitness functions. The combination of a conformity-based PTV fitness function and a dose-volume histogram (DVH) or equivalent uniform dose (EUD) -based fitness function for the OAR produced relatively uniform and conformal PTV doses, with well-spaced beams. A penalty function added to the fitness functions eliminates hotspots. Comparison of resulting DVHs to those from treatment plans developed with a single-objective fluence optimizer (from a commercial treatment planning system) showed good correlation. Results also indicated that pareto shows

  16. PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning.

    Science.gov (United States)

    Fiege, Jason; McCurdy, Boyd; Potrebko, Peter; Champion, Heather; Cull, Andrew

    2011-09-01

    In radiation therapy treatment planning, the clinical objectives of uniform high dose to the planning target volume (PTV) and low dose to the organs-at-risk (OARs) are invariably in conflict, often requiring compromises to be made between them when selecting the best treatment plan for a particular patient. In this work, the authors introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a multiobjective optimization tool to solve for beam angles and fluence patterns in intensity-modulated radiation therapy (IMRT) treatment planning. pareto is built around a powerful multiobjective genetic algorithm (GA), which allows us to treat the problem of IMRT treatment plan optimization as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. We have employed a simple parameterized beam fluence representation with a realistic dose calculation approach, incorporating patient scatter effects, to demonstrate feasibility of the proposed approach on two phantoms. The first phantom is a simple cylindrical phantom containing a target surrounded by three OARs, while the second phantom is more complex and represents a paraspinal patient. pareto results in a large database of Pareto nondominated solutions that represent the necessary trade-offs between objectives. The solution quality was examined for several PTV and OAR fitness functions. The combination of a conformity-based PTV fitness function and a dose-volume histogram (DVH) or equivalent uniform dose (EUD) -based fitness function for the OAR produced relatively uniform and conformal PTV doses, with well-spaced beams. A penalty function added to the fitness functions eliminates hotspots. Comparison of resulting DVHs to those from treatment plans developed with a single-objective fluence optimizer (from a commercial treatment planning system) showed good correlation. Results also indicated that pareto shows promise in optimizing the number

  17. Quality assurance for high dose rate brachytherapy treatment planning optimization: using a simple optimization to verify a complex optimization

    International Nuclear Information System (INIS)

    Deufel, Christopher L; Furutani, Keith M

    2014-01-01

    As dose optimization for high dose rate brachytherapy becomes more complex, it becomes increasingly important to have a means of verifying that optimization results are reasonable. A method is presented for using a simple optimization as quality assurance for the more complex optimization algorithms typically found in commercial brachytherapy treatment planning systems. Quality assurance tests may be performed during commissioning, at regular intervals, and/or on a patient specific basis. A simple optimization method is provided that optimizes conformal target coverage using an exact, variance-based, algebraic approach. Metrics such as dose volume histogram, conformality index, and total reference air kerma agree closely between simple and complex optimizations for breast, cervix, prostate, and planar applicators. The simple optimization is shown to be a sensitive measure for identifying failures in a commercial treatment planning system that are possibly due to operator error or weaknesses in planning system optimization algorithms. Results from the simple optimization are surprisingly similar to the results from a more complex, commercial optimization for several clinical applications. This suggests that there are only modest gains to be made from making brachytherapy optimization more complex. The improvements expected from sophisticated linear optimizations, such as PARETO methods, will largely be in making systems more user friendly and efficient, rather than in finding dramatically better source strength distributions. (paper)

  18. The optimized expansion based low-rank method for wavefield extrapolation

    KAUST Repository

    Wu, Zedong

    2014-03-01

    Spectral methods are fast becoming an indispensable tool for wavefield extrapolation, especially in anisotropic media because it tends to be dispersion and artifact free as well as highly accurate when solving the wave equation. However, for inhomogeneous media, we face difficulties in dealing with the mixed space-wavenumber domain extrapolation operator efficiently. To solve this problem, we evaluated an optimized expansion method that can approximate this operator with a low-rank variable separation representation. The rank defines the number of inverse Fourier transforms for each time extrapolation step, and thus, the lower the rank, the faster the extrapolation. The method uses optimization instead of matrix decomposition to find the optimal wavenumbers and velocities needed to approximate the full operator with its explicit low-rank representation. As a result, we obtain lower rank representations compared with the standard low-rank method within reasonable accuracy and thus cheaper extrapolations. Additional bounds set on the range of propagated wavenumbers to adhere to the physical wave limits yield unconditionally stable extrapolations regardless of the time step. An application on the BP model provided superior results compared to those obtained using the decomposition approach. For transversely isotopic media, because we used the pure P-wave dispersion relation, we obtained solutions that were free of the shear wave artifacts, and the algorithm does not require that n > 0. In addition, the required rank for the optimization approach to obtain high accuracy in anisotropic media was lower than that obtained by the decomposition approach, and thus, it was more efficient. A reverse time migration result for the BP tilted transverse isotropy model using this method as a wave propagator demonstrated the ability of the algorithm.

  19. MO-B-BRB-00: Optimizing the Treatment Planning Process

    International Nuclear Information System (INIS)

    2015-01-01

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  20. MO-B-BRB-00: Optimizing the Treatment Planning Process

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  1. Optimal partial-arcs in VMAT treatment planning

    International Nuclear Information System (INIS)

    Wala, Jeremiah; Salari, Ehsan; Chen Wei; Craft, David

    2012-01-01

    We present a method for improving the delivery efficiency of VMAT by extending the recently published VMAT treatment planning algorithm vmerge to automatically generate optimal partial-arc plans. A high-quality initial plan is created by solving a convex multicriteria optimization problem using 180 equi-spaced beams. This initial plan is used to form a set of dose constraints, and a set of partial-arc plans is created by searching the space of all possible partial-arc plans that satisfy these constraints. For each partial-arc, an iterative fluence map merging and sequencing algorithm (vmerge) is used to improve the delivery efficiency. Merging continues as long as the dose quality is maintained above a user-defined threshold. The final plan is selected as the partial-arc with the lowest treatment time. The complete algorithm is called pmerge. Partial-arc plans are created using pmerge for a lung, liver and prostate case, with final treatment times of 127, 245 and 147 s. Treatment times using full arcs with vmerge are 211, 357 and 178 s. The mean doses to the critical structures for the vmerge and pmerge plans are kept within 5% of those in the initial plan, and the target volume covered by the prescription isodose is maintained above 98% for the pmerge and vmerge plans. Additionally, we find that the angular distribution of fluence in the initial plans is predictive of the start and end angles of the optimal partial-arc. We conclude that VMAT delivery efficiency can be improved by employing partial-arcs without compromising dose quality, and that partial-arcs are most applicable to cases with non-centralized targets. (paper)

  2. State Environmental Policy Act (SEPA) Environmental Checklist Form 216-B-3 Expansion Ponds Closure Plan

    International Nuclear Information System (INIS)

    1993-12-01

    The 216-B-3 Expansion Ponds Closure Plan (Revision 1) consists of a Part A Dangerous Waste Permit Application and a Resource Conservation and Recovery Act Closure Plan. An explanation of the Part A submitted with this document is provided at the beginning of the Part A Section. The closure plan consists of nine chapters and five appendices. The 216-B-3 Pond System consists of a series of four earthen, unlined, interconnected ponds and the 216-B-3-3 Ditch that receive waste water from various 200 East Area operating facilities. These four ponds, collectively. Waste water (primarily cooling water, steam condensate, and sanitary water) from various 200 East Area facilities is discharged to the 216-B-3-3 Ditch. Water discharged to the 216-8-3-3 Ditch flows directly into the 216-B-3 Pond. In the past, waste water discharges to B Pond and the 216-B-3-3 Ditch contained mixed waste (radioactive waste and dangerous waste). The radioactive portion of mixed waste has been interpreted by the US Department of Energy (DOE) to be regulated under the Atomic Energy Act of 1954; the nonradioactive dangerous portion of mixed waste is regulated under RCRA. Mixed waste also may be considered a hazardous substance under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA) when considering remediation of waste sites

  3. Generation Expansion Planning in pool market: A hybrid modified game theory and improved genetic algorithm

    International Nuclear Information System (INIS)

    Shayanfar, H.A.; Lahiji, A. Saliminia; Aghaei, J.; Rabiee, A.

    2009-01-01

    Unlike the traditional policy, Generation Expansion Planning (GEP) problem in competitive framework is complicated. In the new policy, each Generation Company (GENCO) decides to invest in such a way that obtains as much profit as possible. This paper presents a new hybrid algorithm to determine GEP in a Pool market. The proposed algorithm is divided in two programming levels: master and slave. In the master level a Modified Game Theory (MGT) is proposed to evaluate the contrast of GENCOs by the Independent System Operator (ISO). In the slave level, an Improved Genetic Algorithm (IGA) method is used to find the best solution of each GENCO for decision-making of investment. The validity of the proposed method is examined in the case study including three GENCOs with multi-type of power plants. The results show that the presented method is both satisfactory and consistent with expectation. (author)

  4. Optimization of stereotactic body radiotherapy treatment planning using a multicriteria optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Ghandour, Sarah; Cosinschi, Adrien; Mazouni, Zohra; Pachoud, Marc; Matzinger, Oscar [Riviera-Chablais Hospital, Vevey (Switzerland). Cancer Center, Radiotherapy Dept.

    2016-07-01

    To provide high-quality and efficient dosimetric planning for various types of stereotactic body radiotherapy (SBRT) for tumor treatment using a multicriteria optimization (MCO) technique fine-tuned with direct machine parameter optimization (DMPO). Eighteen patients with lung (n = 11), liver (n = 5) or adrenal cell cancer (n = 2) were treated using SBRT in our clinic between December 2014 and June 2015. Plans were generated using the RayStation trademark Treatment Planning System (TPS) with the VMAT technique. Optimal deliverable SBRT plans were first generated using an MCO algorithm to find a well-balanced tradeoff between tumor control and normal tissue sparing in an efficient treatment planning time. Then, the deliverable plan was post-processed using the MCO solution as the starting point for the DMPO algorithm to improve the dose gradient around the planning target volume (PTV) while maintaining the clinician's priorities. The dosimetric quality of the plans was evaluated using dose-volume histogram (DVH) parameters, which account for target coverage and the sparing of healthy tissue, as well as the CI100 and CI50 conformity indexes. Using a combination of the MCO and DMPO algorithms showed that the treatment plans were clinically optimal and conformed to all organ risk dose volume constraints reported in the literature, with a computation time of approximately one hour. The coverage of the PTV (D99% and D95%) and sparing of organs at risk (OAR) were similar between the MCO and MCO + DMPO plans, with no significant differences (p > 0.05) for all the SBRT plans. The average CI100 and CI50 values using MCO + DMPO were significantly better than those with MCO alone (p < 0.05). The MCO technique allows for convergence on an optimal solution for SBRT within an efficient planning time. The combination of the MCO and DMPO techniques yields a better dose gradient, especially for lung tumors.

  5. TECHNIQUE OF OPTIMAL AUDIT PLANNING FOR INFORMATION SECURITY MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    F. N. Shago

    2014-03-01

    Full Text Available Complication of information security management systems leads to the necessity of improving the scientific and methodological apparatus for these systems auditing. Planning is an important and determining part of information security management systems auditing. Efficiency of audit will be defined by the relation of the reached quality indicators to the spent resources. Thus, there is an important and urgent task of developing methods and techniques for optimization of the audit planning, making it possible to increase its effectiveness. The proposed technique gives the possibility to implement optimal distribution for planning time and material resources on audit stages on the basis of dynamics model for the ISMS quality. Special feature of the proposed approach is the usage of a priori data as well as a posteriori data for the initial audit planning, and also the plan adjustment after each audit event. This gives the possibility to optimize the usage of audit resources in accordance with the selected criteria. Application examples of the technique are given while planning audit information security management system of the organization. The result of computational experiment based on the proposed technique showed that the time (cost audit costs can be reduced by 10-15% and, consequently, quality assessments obtained through audit resources allocation can be improved with respect to well-known methods of audit planning.

  6. Planning for a major expansion of the olympic dam copper/uranium resource in South Australia

    International Nuclear Information System (INIS)

    Higgins, R. J.

    2006-01-01

    Full text: Full text: The polymetallic Olympic Dam deposit in northern South Australia contains the world's largest known economic uranium resource. The current resource estimate is 3,970 million tones at 0.4 kg/t U308. Uranium is a co-product of an existing operation that also produces copper, gold and silver. Production began in 1998. Ore mined in 2006 is expected to be close to 10 million tones to produce 4,500 tonnes of uranium oxide and 220,000 tonnes of copper cathode. BHP Billiton is undertaking a pre-feasibility study into expanding annual production capacity to about 15,000 tonnes of uranium and 500,000 tonnes copper. Subject to successful completion of the pre-feasibility study and a final feasibility study, construction of the expansion could begin by early 2009, with the expanded production capacity being commissioned in 2013. The resource estimate has been significantly increased by drilling of the so-far undeveloped southern section of the orebody. Current planning indicates that this section could be mined by open pit. Ore is at depth and extends from 350 metres to about 1000 metres below surface. The existing operations facilities at Olympic Dam comprise an underground mine, and a mineral processing plant and associated infrastructure which would be expanded to support expanded mining. Major items of infrastructure could include a new powerline, water pipeline and associated coastal desalination plant, a rail link to Olympic Dam from the existing national network and further development of the Roxby Downs township (current population 4,000). The operation is regulated by an Indenture Agreement with the South Australian Government. To enable the expansion to proceed, the Indenture Agreement will be renegotiated. The operation is also regulated by the Federal Government. An Environmental Impact Statement is being developed to secure the necessary State and Federal approvals. A land access agreement is being negotiated with indigenous groups. Plans for

  7. Plug pattern optimization for gamma knife radiosurgery treatment planning

    International Nuclear Information System (INIS)

    Zhang Pengpeng; Wu, Jackie; Dean, David; Xing Lei; Xue Jinyue; Maciunas, Robert; Sibata, Claudio

    2003-01-01

    Purpose: To develop a novel dose optimization algorithm for improving the sparing of critical structures during gamma knife radiosurgery by shaping the plug pattern of each individual shot. Method and Materials: We first use a geometric information (medial axis) aided guided evolutionary simulated annealing (GESA) optimization algorithm to determine the number of shots and isocenter location, size, and weight of each shot. Then we create a plug quality score system that checks the dose contribution to the volume of interest by each plug in the treatment plan. A positive score implies that the corresponding source could be open to improve tumor coverage, whereas a negative score means the source could be blocked for the purpose of sparing normal and critical structures. The plug pattern is then optimized via the GESA algorithm that is integrated with this score system. Weight and position of each shot are also tuned in this procedure. Results: An acoustic tumor case is used to evaluate our algorithm. Compared to the treatment plan generated without plug patterns, adding an optimized plug pattern into the treatment planning process boosts tumor coverage index from 95.1% to 97.2%, reduces RTOG conformity index from 1.279 to 1.167, lowers Paddick's index from 1.34 to 1.20, and trims the critical structure receiving more than 30% maximum dose from 16 mm 3 to 6 mm 3 . Conclusions: Automated GESA-based plug pattern optimization of gamma knife radiosurgery frees the treatment planning team from the manual forward planning procedure and provides an optimal treatment plan

  8. Planning model for hydraulic and thermic generation systems expansion under uncertainly conditions and financial restrictions; Modelo de planejamento da expansao de sistemas hidrotermicos sob incertezas e restricoes financeiras

    Energy Technology Data Exchange (ETDEWEB)

    Gorenstin, B.G.; Costa, J.P. da [CEPEL, Rio de Janeiro, RJ (Brazil); Pereira, M.V.F.; Campodonico, N.M.

    1993-12-31

    This issue presents a methodology for planning the systems expansion of hydraulic and thermic power generation associated considering several uncertainly factors, such as: demand growing, fuel costs, delays on the work construction, financial restrictions, etc. The solution focus is based on stock optimize techniques, decision analysis. This work is being developed by the Brazilian Electrical Centre (ELETROBRAS) and rely on the Energy Latin-American Organization (OLADE), Development Inter-American Bank (BID), World Bank (BIRD) and International Energy Agency (IAEA) support. An example case with Costa Rica system is also discussed 19 refs., 4 figs., 2 tabs.

  9. Water supply as a constraint on transmission expansion planning in the Western interconnection

    Science.gov (United States)

    Tidwell, Vincent C.; Bailey, Michael; Zemlick, Katie M.; Moreland, Barbara D.

    2016-12-01

    Consideration of water supply in transmission expansion planning (TEP) provides a valuable means of managing impacts of thermoelectric generation on limited water resources. Toward this opportunity, thermoelectric water intensity factors and water supply availability (fresh and non-fresh sources) were incorporated into a recent TEP exercise conducted for the electric interconnection in the Western United States. The goal was to inform the placement of new thermoelectric generation so as to minimize issues related to water availability. Although freshwater availability is limited in the West, few instances across five TEP planning scenarios were encountered where water availability impacted the development of new generation. This unexpected result was related to planning decisions that favored the development of low water use generation that was geographically dispersed across the West. These planning decisions were not made because of their favorable influence on thermoelectric water demand; rather, on the basis of assumed future fuel and technology costs, policy drivers and the topology of electricity demand. Results also projected that interconnection-wide thermoelectric water consumption would increase by 31% under the business-as-usual case, while consumption would decrease by 42% under a scenario assuming a low-carbon future. Except in a few instances, new thermoelectric water consumption could be accommodated with less than 10% of the local available water supply; however, limited freshwater supplies and state-level policies could increase use of non-fresh water sources for new thermoelectric generation. Results could have been considerably different if scenarios favoring higher-intensity water use generation technology or potential impacts of climate change had been explored. Conduct of this exercise highlighted the importance of integrating water into all phases of TEP, particularly joint management of decisions that are both directly (e.g., water

  10. Feasibility of identification of gamma knife planning strategies by identification of pareto optimal gamma knife plans.

    Science.gov (United States)

    Giller, C A

    2011-12-01

    The use of conformity indices to optimize Gamma Knife planning is common, but does not address important tradeoffs between dose to tumor and normal tissue. Pareto analysis has been used for this purpose in other applications, but not for Gamma Knife (GK) planning. The goal of this work is to use computer models to show that Pareto analysis may be feasible for GK planning to identify dosimetric tradeoffs. We define a GK plan A to be Pareto dominant to B if the prescription isodose volume of A covers more tumor but not more normal tissue than B, or if A covers less normal tissue but not less tumor than B. A plan is Pareto optimal if it is not dominated by any other plan. Two different Pareto optimal plans represent different tradeoffs between dose to tumor and normal tissue, because neither plan dominates the other. 'GK simulator' software calculated dose distributions for GK plans, and was called repetitively by a genetic algorithm to calculate Pareto dominant plans. Three irregular tumor shapes were tested in 17 trials using various combinations of shots. The mean number of Pareto dominant plans/trial was 59 ± 17 (sd). Different planning strategies were identified by large differences in shot positions, and 70 of the 153 coordinate plots (46%) showed differences of 5mm or more. The Pareto dominant plans dominated other nearby plans. Pareto dominant plans represent different dosimetric tradeoffs and can be systematically calculated using genetic algorithms. Automatic identification of non-intuitive planning strategies may be feasible with these methods.

  11. Software for CATV Design and Frequency Plan Optimization

    Directory of Open Access Journals (Sweden)

    O. Hala

    2007-09-01

    Full Text Available The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

  12. Model of clinker capacity expansion

    CSIR Research Space (South Africa)

    Stylianides, T

    1998-10-01

    Full Text Available This paper describes a model which has been applied in practice to determine an optimal plan for clinker capacity expansion. The problem was formulated as an integer linear program aiming to determine the optimal number, size and location of kilns...

  13. Robust Optimization Model for Production Planning Problem under Uncertainty

    Directory of Open Access Journals (Sweden)

    Pembe GÜÇLÜ

    2017-01-01

    Full Text Available Conditions of businesses change very quickly. To take into account the uncertainty engendered by changes has become almost a rule while planning. Robust optimization techniques that are methods of handling uncertainty ensure to produce less sensitive results to changing conditions. Production planning, is to decide from which product, when and how much will be produced, with a most basic definition. Modeling and solution of the Production planning problems changes depending on structure of the production processes, parameters and variables. In this paper, it is aimed to generate and apply scenario based robust optimization model for capacitated two-stage multi-product production planning problem under parameter and demand uncertainty. With this purpose, production planning problem of a textile company that operate in İzmir has been modeled and solved, then deterministic scenarios’ and robust method’s results have been compared. Robust method has provided a production plan that has higher cost but, will result close to feasible and optimal for most of the different scenarios in the future.

  14. A decision support system for generation expansion planning in competitive electricity markets

    International Nuclear Information System (INIS)

    Pereira, Adelino J.C.; Saraiva, Joao Tome

    2010-01-01

    This paper describes an approach to address the generation expansion-planning problem in order to help generation companies to decide whether to invest on new assets. This approach was developed in the scope of the implementation of electricity markets that eliminated the traditional centralized planning and lead to the creation of several generation companies competing for the delivery of power. As a result, this activity is more risky than in the past and so it is important to develop decision support tools to help generation companies to adequately analyse the available investment options in view of the possible behavior of other competitors. The developed model aims at maximizing the expected revenues of a generation company while ensuring the safe operation of the power system and incorporating uncertainties related with price volatility, with the reliability of generation units, with the demand evolution and with investment and operation costs. These uncertainties are modeled by pdf functions and the solution approach is based on Genetic Algorithms. Finally, the paper includes a Case Study to illustrate the application and interest of the developed approach. (author)

  15. A decision support system for generation expansion planning in competitive electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Adelino J.C. [Departamento de Engenharia Electrotecnica, Instituto Superior de Engenharia de Coimbra, Instituto Politecnico de Coimbra, Rua Pedro Nunes, 3030-199 Coimbra (Portugal); Saraiva, Joao Tome [INESC Porto and Departamento de Engenharia Electrotecnica e Computadores, Faculdade de Engenharia da Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, 4200-465 Porto (Portugal)

    2010-07-15

    This paper describes an approach to address the generation expansion-planning problem in order to help generation companies to decide whether to invest on new assets. This approach was developed in the scope of the implementation of electricity markets that eliminated the traditional centralized planning and lead to the creation of several generation companies competing for the delivery of power. As a result, this activity is more risky than in the past and so it is important to develop decision support tools to help generation companies to adequately analyse the available investment options in view of the possible behavior of other competitors. The developed model aims at maximizing the expected revenues of a generation company while ensuring the safe operation of the power system and incorporating uncertainties related with price volatility, with the reliability of generation units, with the demand evolution and with investment and operation costs. These uncertainties are modeled by pdf functions and the solution approach is based on Genetic Algorithms. Finally, the paper includes a Case Study to illustrate the application and interest of the developed approach. (author)

  16. Inverse planning and optimization: a comparison of solutions

    Energy Technology Data Exchange (ETDEWEB)

    Ringor, Michael [School of Health Sciences, Purdue University, West Lafayette, IN (United States); Papiez, Lech [Department of Radiation Oncology, Indiana University, Indianapolis, IN (United States)

    1998-09-01

    The basic problem in radiation therapy treatment planning is to determine an appropriate set of treatment parameters that would induce an effective dose distribution inside a patient. One can approach this task as an inverse problem, or as an optimization problem. In this presentation, we compare both approaches. The inverse problem is presented as a dose reconstruction problem similar to tomography reconstruction. We formulate the optimization problem as linear and quadratic programs. Explicit comparisons are made between the solutions obtained by inversion and those obtained by optimization for the case in which scatter and attenuation are ignored (the NS-NA approximation)

  17. GPU-Monte Carlo based fast IMRT plan optimization

    Directory of Open Access Journals (Sweden)

    Yongbao Li

    2014-03-01

    Full Text Available Purpose: Intensity-modulated radiation treatment (IMRT plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow.Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, a rough dose calculation is conducted with only a few number of particle per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final result.Results: For a lung case with 5317 beamlets, 105 particles per beamlet in the first round, and 108 particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec.Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.--------------------------------Cite this article as: Li Y, Tian Z

  18. Efficacy of robust optimization plan with partial-arc VMAT for photon volumetric-modulated arc therapy: A phantom study.

    Science.gov (United States)

    Miura, Hideharu; Ozawa, Shuichi; Nagata, Yasushi

    2017-09-01

    This study investigated position dependence in planning target volume (PTV)-based and robust optimization plans using full-arc and partial-arc volumetric modulated arc therapy (VMAT). The gantry angles at the periphery, intermediate, and center CTV positions were 181°-180° (full-arc VMAT) and 181°-360° (partial-arc VMAT). A PTV-based optimization plan was defined by 5 mm margin expansion of the CTV to a PTV volume, on which the dose constraints were applied. The robust optimization plan consisted of a directly optimized dose to the CTV under a maximum-uncertainties setup of 5 mm. The prescription dose was normalized to the CTV D 99% (the minimum relative dose that covers 99% of the volume of the CTV) as an original plan. The isocenter was rigidly shifted at 1 mm intervals in the anterior-posterior (A-P), superior-inferior (S-I), and right-left (R-L) directions from the original position to the maximum-uncertainties setup of 5 mm in the original plan, yielding recalculated dose distributions. It was found that for the intermediate and center positions, the uncertainties in the D 99% doses to the CTV for all directions did not significantly differ when comparing the PTV-based and robust optimization plans (P > 0.05). For the periphery position, uncertainties in the D 99% doses to the CTV in the R-L direction for the robust optimization plan were found to be lower than those in the PTV-based optimization plan (P plan's efficacy using partial-arc VMAT depends on the periphery CTV position. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

  19. Incorporating environmental externalities into the capacity expansion planning: An Israeli case study

    International Nuclear Information System (INIS)

    Becker, Nir; Soloveitchik, David; Olshansky, Moshe

    2011-01-01

    Highlights: → Long term energy-environmental planning problems for the electricity sector. → Environmental considerations in the capacity expansion plan. → Modified version of WASP-IV as a multiple objective programming model. → Multi-objective analysis of trade-offs between costs and pollutants reduction. -- Abstract: In this paper we use the WASP-IV model and develop methodology to estimate the impact of several environmental externality costs on the electricity sector development plan. For this purpose, 22 cases were generated which were later on reduced to only seven non-dominated cases by considering this problem as a dynamic multiple objective programming model. The major impact of internalizing the external cost is on fuel use. In the electricity generation system more natural gas and less coal has been used. A cost benefit analysis (CBA) of three scenarios has been performed focusing on taxing only one pollutant while looking at its overall implication. The benefit cost ratio was about 4.5 while the net benefit was about 200 million USD (depending on the scenario). Multi-objective analysis among the different scenarios was carried in a dynamic setting. Seven scenarios appear in the non-dominated set. Out of them five appears in every year and those should have a higher weight placed on them by policy makers. Out of those five, two are a single tax on one pollutant. Thus, policy makers might want to consider a mixture of taxes but for the sake of simplicity can also use a simple one tax on a given pollutant.

  20. Optimal day-ahead operational planning of microgrids

    International Nuclear Information System (INIS)

    Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad; Siano, Pierluigi

    2016-01-01

    Highlights: • A new multi-objective model for optimal day-ahead operational planning of microgrids is proposed. • A new concept called seamlessness is introduced to control the sustainability of microgrid. • A new method is developed to manage the load and renewable energy resources estimation errors. • A new solution based on a combination of numerical and evolutionary approaches is proposed. - Abstract: Providing a cost-efficient, eco-friendly and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of microgrid technology have provided huge potentials while distributing electricity more effectively, economically and securely. Accordingly, this paper presents a new multi-objective generation management model for optimal day-ahead operational planning of medium voltage microgrids. The proposed model optimizes both pollutant emission and operating cost of a microgrid by using multi-objective optimization. Besides, a seamlessness-selective algorithm is integrated into the model, which can be adopted to achieve the desired self-sufficiency level for microgrids along a specified planning horizon. Furthermore, the model is characterized by a reserve-assessment strategy developed to handle the load and renewable energy resources estimation errors. The introduced model is solved using a combination of numerical and evolutionary methods of species-based quantum particle swarm optimization to find the optimal scheduling scheme and minos-based optimal power flow to optimize the operating cost and emission. In addition, the suggested solution approach also incorporates an efficient mechanism for considering energy storage systems and coding the candidate solutions in the evolutionary algorithm. The proposed model is implemented on a test microgrid and is investigated through simulations to study the different aspects of the problem. The results show significant improvements and benefits which are obtained by

  1. Optimal farm plans for sustainable environmental and economic ...

    African Journals Online (AJOL)

    The optimal farm plans indicated that the cassava/maize intercrop gave the best results in Ijemo-Fadipe and Ajura, while the cassava/melon and sole cassava enterprises were best in Ijale-Papa and Ilewo-Orile respectively. Operating expenses was found to be the most limiting factors in all the villages. The study concluded ...

  2. Constrained optimal motion planning for autonomous vehicles using PRONTO

    NARCIS (Netherlands)

    Aguiar, A.P.; Bayer, F.A.; Hauser, J.; Häusler, A.J.; Notarstefano, G.; Pascoal, A.M.; Rucco, A.; Saccon, A.

    2017-01-01

    This chapter provides an overview of the authors’ efforts in vehicle trajectory exploration and motion planning based on PRONTO, a numerical method for solving optimal control problems developed over the last two decades. The chapter reviews the basics of PRONTO, providing the appropriate references

  3. Resampling: An optimization method for inverse planning in robotic radiosurgery

    International Nuclear Information System (INIS)

    Schweikard, Achim; Schlaefer, Alexander; Adler, John R. Jr.

    2006-01-01

    By design, the range of beam directions in conventional radiosurgery are constrained to an isocentric array. However, the recent introduction of robotic radiosurgery dramatically increases the flexibility of targeting, and as a consequence, beams need be neither coplanar nor isocentric. Such a nonisocentric design permits a large number of distinct beam directions to be used in one single treatment. These major technical differences provide an opportunity to improve upon the well-established principles for treatment planning used with GammaKnife or LINAC radiosurgery. With this objective in mind, our group has developed over the past decade an inverse planning tool for robotic radiosurgery. This system first computes a set of beam directions, and then during an optimization step, weights each individual beam. Optimization begins with a feasibility query, the answer to which is derived through linear programming. This approach offers the advantage of completeness and avoids local optima. Final beam selection is based on heuristics. In this report we present and evaluate a new strategy for utilizing the advantages of linear programming to improve beam selection. Starting from an initial solution, a heuristically determined set of beams is added to the optimization problem, while beams with zero weight are removed. This process is repeated to sample a set of beams much larger compared with typical optimization. Experimental results indicate that the planning approach efficiently finds acceptable plans and that resampling can further improve its efficiency

  4. Classical-Equivalent Bayesian Portfolio Optimization for Electricity Generation Planning

    Directory of Open Access Journals (Sweden)

    Hellinton H. Takada

    2018-01-01

    Full Text Available There are several electricity generation technologies based on different sources such as wind, biomass, gas, coal, and so on. The consideration of the uncertainties associated with the future costs of such technologies is crucial for planning purposes. In the literature, the allocation of resources in the available technologies has been solved as a mean-variance optimization problem assuming knowledge of the expected values and the covariance matrix of the costs. However, in practice, they are not exactly known parameters. Consequently, the obtained optimal allocations from the mean-variance optimization are not robust to possible estimation errors of such parameters. Additionally, it is usual to have electricity generation technology specialists participating in the planning processes and, obviously, the consideration of useful prior information based on their previous experience is of utmost importance. The Bayesian models consider not only the uncertainty in the parameters, but also the prior information from the specialists. In this paper, we introduce the classical-equivalent Bayesian mean-variance optimization to solve the electricity generation planning problem using both improper and proper prior distributions for the parameters. In order to illustrate our approach, we present an application comparing the classical-equivalent Bayesian with the naive mean-variance optimal portfolios.

  5. Spatiotemporal radiotherapy planning using a global optimization approach

    Science.gov (United States)

    Adibi, Ali; Salari, Ehsan

    2018-02-01

    This paper aims at quantifying the extent of potential therapeutic gain, measured using biologically effective dose (BED), that can be achieved by altering the radiation dose distribution over treatment sessions in fractionated radiotherapy. To that end, a spatiotemporally integrated planning approach is developed, where the spatial and temporal dose modulations are optimized simultaneously. The concept of equivalent uniform BED (EUBED) is used to quantify and compare the clinical quality of spatiotemporally heterogeneous dose distributions in target and critical structures. This gives rise to a large-scale non-convex treatment-plan optimization problem, which is solved using global optimization techniques. The proposed spatiotemporal planning approach is tested on two stylized cancer cases resembling two different tumor sites and sensitivity analysis is performed for radio-biological and EUBED parameters. Numerical results validate that spatiotemporal plans are capable of delivering a larger BED to the target volume without increasing the BED in critical structures compared to conventional time-invariant plans. In particular, this additional gain is attributed to the irradiation of different regions of the target volume at different treatment sessions. Additionally, the trade-off between the potential therapeutic gain and the number of distinct dose distributions is quantified, which suggests a diminishing marginal gain as the number of dose distributions increases.

  6. Clinical grade purification and expansion of NK cell products for an optimized manufacturing protocol

    Directory of Open Access Journals (Sweden)

    Ulrike eKoehl

    2013-05-01

    Full Text Available Allogeneic Natural Killer (NK cells are used for adoptive immunotherapy after stem cell transplantation. In order to overcome technical limitations in NK cell purification and activation, the following study investigates the impact of different variables on NK cell recovery, cytotoxicity and T cell depletion during GMP-grade NK cell selection. 40 NK cell products were derived from 54 unstimulated donor leukaphereses using immunomagnetic CD3 T-cell depletion, followed by a CD56 cell enrichment step. For T cell depletion, either the depletion 2.1 program in single or double procedure (D2.1 1depl, n=18; D2.1 2depl, n=13 or the faster depletion 3.1 (D3.1, n=9 was used on the CliniMACS instrument. 17 purified NK cell products were activated in vitro by IL-2 for 12 days. The whole process resulted in a median number of 7.59x10e8 CD56+CD3- cells with both purity and viability of 94%, respectively. The T-cell depletion was significantly better using D2.1 1depl/2depl compared to D3.1 (log 4.6/log 4.9 vs. log 3.7; p<0.01 and double procedure in two stages led always to residual T cells below 0.1%. In contrast D3.1 was superior to D2.1 1depl/2depl with regard to recovery of CD56+CD3- NK cells (68% vs 41%/38%. Concomitant monocytes and especially IL-2 activation led to increased NK cell activity against malignant target cells compared to unstimulated NK cells, which correlated with both up-regulation of natural cytotoxicity receptors and intracellular signaling. Overall, wide variations in the NK cell expansion rate and the distribution of NK cell subpopulations were found. In conclusion, our results indicate that GMP-grade purification of NK cells might be improved by a sequential processing of T cell depletion program D2.1 and D3.1. In addition NK cell expansion protocols need to be further optimized.

  7. Development of a fast optimization preview in radiation treatment planning

    International Nuclear Information System (INIS)

    Hoeffner, J.; Decker, P.; Schmidt, E.L.; Herbig, W.; Rittler, J.; Weiss, P.

    1996-01-01

    Usually, the speed of convergence of some iterative algorithms is restricted to a bounded relaxation parameter. Exploiting the special altering behavior of the weighting factors at each step, many iteration steps are avoided by overrelaxing this relaxation parameter. Therefore, the relaxation parameter is increased as long as the optimization result is improved. This can be performed without loss of accuracy. Our optimization technique is demonstrated by the case of a right lung carcinoma. The solution space for this case is 36 isocentric X-ray beams evenly spaced at 10 . Each beam is restricted to 23 MV X-ray fields with a planning target volume matched by irregular field shapes, similar to that produced by a multileaf collimator. Four organs at risk plus the planning target volume are considered in the optimization process. The convergence behavior of the optimization algorithm is shown by overrelaxing the relaxation parameter in comparison to conventional relaxation parameter control. The new approach offers the ability to get a fast preview of the expected final result. If the clinician is in agreement with the preview, the algorithm is continued and achieves the result proven by the Cimmino optimization algorithm. In the other case, if the clinician doesn't agree with the preview, he will be able to change the optimization parameters (e.g. field entry points) and to restart the algorithm. (orig./MG) [de

  8. Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

    International Nuclear Information System (INIS)

    Niu Ying; Zhang Guowei; Berman, Barry L.; Parke, William C.; Yi Byongyong; Yu, Cedric X.

    2012-01-01

    Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors’ POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors’ POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

  9. Planning the expansion of transmission with evolutionary programming; Planeacion de la expansion de transmision con programacion evolutiva

    Energy Technology Data Exchange (ETDEWEB)

    Ceciliano Meza, Jose Luis; Nieva Gomez, Rolando [Instituto de Investigaciones Electricas, Temixco, Morelos (Mexico)

    1999-07-01

    A method of evolutionary programming for the planning of transmission networks in electrical power systems is presented. This is a whole problem mixed and nonlinear, with a combinatory nature that leads to a very large number of possible solutions for electrical systems of medium and large scale. The problem of transmission planning is described briefly and later it is formulated in mathematical terms. The proposed algorithm of evolutionary programming is applied to a large scale network that is representative of the Mexican electrical system. [Spanish] Se presenta un metodo de programacion evolutiva para la planeacion de redes de transmision en sistemas electricos de potencia. Este es un problema entero mixto y no lineal, con una naturaleza combinatoria que conduce a un numero muy grande de soluciones posibles para sistemas electricos de mediana y gran escala. Se describe brevemente el problema de planeacion de transmision y posteriormente se formula en terminos matematicos. El algoritmo propuesto de programacion evolutiva se aplica a una red electrica de gran escala que es representativa del sistema electrico Mexicano.

  10. Fleet Planning Decision-Making: Two-Stage Optimization with Slot Purchase

    Directory of Open Access Journals (Sweden)

    Lay Eng Teoh

    2016-01-01

    Full Text Available Essentially, strategic fleet planning is vital for airlines to yield a higher profit margin while providing a desired service frequency to meet stochastic demand. In contrast to most studies that did not consider slot purchase which would affect the service frequency determination of airlines, this paper proposes a novel approach to solve the fleet planning problem subject to various operational constraints. A two-stage fleet planning model is formulated in which the first stage selects the individual operating route that requires slot purchase for network expansions while the second stage, in the form of probabilistic dynamic programming model, determines the quantity and type of aircraft (with the corresponding service frequency to meet the demand profitably. By analyzing an illustrative case study (with 38 international routes, the results show that the incorporation of slot purchase in fleet planning is beneficial to airlines in achieving economic and social sustainability. The developed model is practically viable for airlines not only to provide a better service quality (via a higher service frequency to meet more demand but also to obtain a higher revenue and profit margin, by making an optimal slot purchase and fleet planning decision throughout the long-term planning horizon.

  11. Optimality of profit-including prices under ideal planning.

    Science.gov (United States)

    Samuelson, P A

    1973-07-01

    Although prices calculated by a constant percentage markup on all costs (nonlabor as well as direct-labor) are usually admitted to be more realistic for a competitive capitalistic model, the view is often expressed that, for optimal planning purposes, the "values" model of Marx's Capital, Volume I, is to be preferred. It is shown here that an optimal-control model that maximizes discounted social utility of consumption per capita and that ultimately approaches a steady state must ultimately have optimal pricing that involves equal rates of steady-state profit in all industries; and such optimal pricing will necessarily deviate from Marx's model of equal rates of surplus value (markups on direct-labor only) in all industries.

  12. Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qianqian; Blohm, Andrew; Liu, Bo

    2017-04-01

    A planning framework is developed to optimize runoff control schemes at scales relevant for regional planning at an early stage. The framework employs less sophisticated modeling approaches to allow a practical application in developing regions with limited data sources and computing capability. The methodology contains three interrelated modules: (1)the geographic information system (GIS)-based hydrological module, which aims at assessing local hydrological constraints and potential for runoff control according to regional land-use descriptions; (2)the grading module, which is built upon the method of fuzzy comprehensive evaluation. It is used to establish a priority ranking system to assist the allocation of runoff control targets at the subdivision level; and (3)the genetic algorithm-based optimization module, which is included to derive Pareto-based optimal solutions for mesolevel allocation with multiple competing objectives. The optimization approach describes the trade-off between different allocation plans and simultaneously ensures that all allocation schemes satisfy the minimum requirement on runoff control. Our results highlight the importance of considering the mesolevel allocation strategy in addition to measures at macrolevels and microlevels in urban runoff management. (C) 2016 American Society of Civil Engineers.

  13. AI-guided parameter optimization in inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach

  14. Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm

    DEFF Research Database (Denmark)

    Awasthi, Abhishek; Venkitusamy, Karthikeyan; Padmanaban, Sanjeevikumar

    2017-01-01

    India's ever increasing population has made it necessary to develop alternative modes of transportation with electric vehicles being the most preferred option. The major obstacle is the deteriorating impact on the utility distribution system brought about by improper setup of these charging...... stations. This paper deals with the optimal planning (siting and sizing) of charging station infrastructure in the city of Allahabad, India. This city is one of the upcoming smart cities, where electric vehicle transportation pilot project is going on under Government of India initiative. In this context......, a hybrid algorithm based on genetic algorithm and improved version of conventional particle swarm optimization is utilized for finding optimal placement of charging station in the Allahabad distribution system. The particle swarm optimization algorithm re-optimizes the received sub-optimal solution (site...

  15. Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT).

    Science.gov (United States)

    Men, Chunhua; Romeijn, H Edwin; Jia, Xun; Jiang, Steve B

    2010-11-01

    To develop a novel aperture-based algorithm for volumetric modulated are therapy (VMAT) treatment plan optimization with high quality and high efficiency. The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequential way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.

  16. An optimization planning technique for Suez Canal Network in Egypt

    Energy Technology Data Exchange (ETDEWEB)

    Abou El-Ela, A.A.; El-Zeftawy, A.A.; Allam, S.M.; Atta, Gasir M. [Electrical Engineering Dept., Faculty of Eng., Shebin El-Kom (Egypt)

    2010-02-15

    This paper introduces a proposed optimization technique POT for predicting the peak load demand and planning of transmission line systems. Many of traditional methods have been presented for long-term load forecasting of electrical power systems. But, the results of these methods are approximated. Therefore, the artificial neural network (ANN) technique for long-term peak load forecasting is modified and discussed as a modern technique in long-term load forecasting. The modified technique is applied on the Egyptian electrical network dependent on its historical data to predict the electrical peak load demand forecasting up to year 2017. This technique is compared with extrapolation of trend curves as a traditional method. The POT is applied also to obtain the optimal planning of transmission lines for the 220 kV of Suez Canal Network (SCN) using the ANN technique. The minimization of the transmission network costs are considered as an objective function, while the transmission lines (TL) planning constraints are satisfied. Zafarana site on the Red Sea coast is considered as an optimal site for installing big wind farm (WF) units in Egypt. So, the POT is applied to plan both the peak load and the electrical transmission of SCN with and without considering WF to develop the impact of WF units on the electrical transmission system of Egypt, considering the reliability constraints which were taken as a separate model in the previous techniques. The application on SCN shows the capability and the efficiently of the proposed techniques to obtain the predicting peak load demand and the optimal planning of transmission lines of SCN up to year 2017. (author)

  17. Optimization of Investment Planning Based on Game-Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Elena Vladimirovna Butsenko

    2018-03-01

    Full Text Available The game-theoretic approach has a vast potential in solving economic problems. On the other hand, the theory of games itself can be enriched by the studies of real problems of decision-making. Hence, this study is aimed at developing and testing the game-theoretic technique to optimize the management of investment planning. This technique enables to forecast the results and manage the processes of investment planning. The proposed method of optimizing the management of investment planning allows to choose the best development strategy of an enterprise. This technique uses the “game with nature” model, and the Wald criterion, the maximum criterion and the Hurwitz criterion as criteria. The article presents a new algorithm for constructing the proposed econometric method to optimize investment project management. This algorithm combines the methods of matrix games. Furthermore, I show the implementation of this technique in a block diagram. The algorithm includes the formation of initial data, the elements of the payment matrix, as well as the definition of maximin, maximal, compromise and optimal management strategies. The methodology is tested on the example of the passenger transportation enterprise of the Sverdlovsk Railway in Ekaterinburg. The application of the proposed methodology and the corresponding algorithm allowed to obtain an optimal price strategy for transporting passengers for one direction of traffic. This price strategy contributes to an increase in the company’s income with minimal risk from the launch of this direction. The obtained results and conclusions show the effectiveness of using the developed methodology for optimizing the management of investment processes in the enterprise. The results of the research can be used as a basis for the development of an appropriate tool and applied by any economic entity in its investment activities.

  18. Triangular Geometrized Sampling Heuristics for Fast Optimal Motion Planning

    Directory of Open Access Journals (Sweden)

    Ahmed Hussain Qureshi

    2015-02-01

    Full Text Available Rapidly-exploring Random Tree (RRT-based algorithms have become increasingly popular due to their lower computational complexity as compared with other path planning algorithms. The recently presented RRT* motion planning algorithm improves upon the original RRT algorithm by providing optimal path solutions. While RRT determines an initial collision-free path fairly quickly, RRT* guarantees almost certain convergence to an optimal, obstacle-free path from the start to the goal points for any given geometrical environment. However, the main limitations of RRT* include its slow processing rate and high memory consumption, due to the large number of iterations required for calculating the optimal path. In order to overcome these limitations, we present another improvement, i.e, the Triangular Geometerized-RRT* (TG-RRT* algorithm, which utilizes triangular geometrical methods to improve the performance of the RRT* algorithm in terms of the processing time and a decreased number of iterations required for an optimal path solution. Simulations comparing the performance results of the improved TG-RRT* with RRT* are presented to demonstrate the overall improvement in performance and optimal path detection.

  19. Energy-Performance as a driver for optimal production planning

    International Nuclear Information System (INIS)

    Salahi, Niloofar; Jafari, Mohsen A.

    2016-01-01

    Highlights: • A 2-dimensional Energy-Performance measure is proposed for energy aware production. • This is a novel approach integrates energy efficiency with production requirements. • This approach simultaneously incorporates machine and process related specifications. • The problem is solved as stochastic MILP with constraints addressing risk averseness. • The optimization is illustrated for 2 cases of single and serial machining operation. • Impact of various electricity pricing schemes on proposed production plan is analyzed. - Abstract: In this paper, we present energy-aware production planning using a two-dimensional “Energy-Performance” measure. With this measure, the production plan explicitly takes into account machine-level requirements, process control strategies, product types and demand patterns. The “Energy-Performance” measure is developed based on an existing concept, namely, “Specific Energy” at machine level. It is further expanded to an “Energy-Performance” profile for a production line. A production planning problem is formulated as a stochastic MILP with risk-averse constraints to account for manufacturer’s risk averseness. The objective is to attain an optimal production plan that minimizes the total loss distribution subject to system throughput targets, probabilistic risk constraints and constraints imposed by the underlying “Energy-Performance” pattern. Electricity price and demand per unit time are assumed to be stochastic. Conditional Value at Risk (CVaR) of loss distributions is used as the manufacturer’s risk measure. Both single-machine and production lines are studied for different profiles and electricity pricing schemes. It is shown that the shape of “Energy-Performance” profile can change optimal plans.

  20. An optimal control approach to manpower planning problem

    Directory of Open Access Journals (Sweden)

    H. W. J. Lee

    2001-01-01

    Full Text Available A manpower planning problem is studied in this paper. The model includes scheduling different types of workers over different tasks, employing and terminating different types of workers, and assigning different types of workers to various trainning programmes. The aim is to find an optimal way to do all these while keeping the time-varying demand for minimum number of workers working on each different tasks satisfied. The problem is posed as an optimal discrete-valued control problem in discrete time. A novel numerical scheme is proposed to solve the problem, and an illustrative example is provided.

  1. An Optimal Turkish Private Pension Plan with a Guarantee Feature

    Directory of Open Access Journals (Sweden)

    Ayşegül İşcanog̃lu-Çekiç

    2016-06-01

    Full Text Available The Turkish Private Pension System is an investment system which aims to generate income for future consumption. This is a volunteer system, and the contributions are held in individual portfolios. Therefore, management of the funds is an important issue for both the participants and the insurance company. In this study, we propose an optimal private pension plan with a guarantee feature that is based on Constant Proportion Portfolio Insurance (CPPI. We derive a closed form formula for the optimal strategy with the help of dynamic programming. Moreover, our model is evaluated with numerical examples, and we compare its performance by implementing a sensitivity analysis.

  2. Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

    Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

  3. Using Optimization Models for Scheduling in Enterprise Resource Planning Systems

    Directory of Open Access Journals (Sweden)

    Frank Herrmann

    2016-03-01

    Full Text Available Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.

  4. Trajectory planning and optimal tracking for an industrial mobile robot

    Science.gov (United States)

    Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

    1994-02-01

    This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

  5. Optimal Multi-Level Lot Sizing for Requirements Planning Systems

    OpenAIRE

    Earle Steinberg; H. Albert Napier

    1980-01-01

    The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

  6. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

    International Nuclear Information System (INIS)

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Jia, Xun; Jiang, Steve; Zhou, Linghong

    2013-01-01

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose–volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30

  7. Visibility-based optimal path and motion planning

    CERN Document Server

    Wang, Paul Keng-Chieh

    2015-01-01

    This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

  8. Optimal pricing and marketing planning for deteriorating items.

    Directory of Open Access Journals (Sweden)

    Seyed Reza Moosavi Tabatabaei

    Full Text Available Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue.

  9. Optimal pricing and marketing planning for deteriorating items

    Science.gov (United States)

    Moosavi Tabatabaei, Seyed Reza; Sadjadi, Seyed Jafar; Makui, Ahmad

    2017-01-01

    Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue. PMID:28306750

  10. Optimal pricing and marketing planning for deteriorating items.

    Science.gov (United States)

    Moosavi Tabatabaei, Seyed Reza; Sadjadi, Seyed Jafar; Makui, Ahmad

    2017-01-01

    Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue.

  11. Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Rangel-Ramirez, Jose G.; Sørensen, John Dalsgaard

    2008-01-01

    , inspection and maintenance activities are developed. This paper considers aspects of inspection and maintenance planning of fatigue prone details in jacket and tripod types of wind turbine support structures. Based oil risk-based inspection planning methods used for oil & gas installations, a framework......Wind turbines for electricity production have increased significantly the last years both in production capability and size. This development is expected to continue also in the coining years. The Support structure for offshore wind turbines is typically a steel structure consisting of a tower...... for optimal inspection and maintenance planning of offshore wind turbines is presented. Special aspects for offshore wind turbines are considered: usually the wind loading are dominating the wave loading, wake effects in wind farms are important and the reliability level is typically significantly lower than...

  12. Motor planning flexibly optimizes performance under uncertainty about task goals.

    Science.gov (United States)

    Wong, Aaron L; Haith, Adrian M

    2017-03-03

    In an environment full of potential goals, how does the brain determine which movement to execute? Existing theories posit that the motor system prepares for all potential goals by generating several motor plans in parallel. One major line of evidence for such theories is that presenting two competing goals often results in a movement intermediate between them. These intermediate movements are thought to reflect an unintentional averaging of the competing plans. However, normative theories suggest instead that intermediate movements might actually be deliberate, generated because they improve task performance over a random guessing strategy. To test this hypothesis, we vary the benefit of making an intermediate movement by changing movement speed. We find that participants generate intermediate movements only at (slower) speeds where they measurably improve performance. Our findings support the normative view that the motor system selects only a single, flexible motor plan, optimized for uncertain goals.

  13. TAX PLANNING: OPTIMIZATION TOOL OF DEBTS TOWARDS THE BUDGET

    Directory of Open Access Journals (Sweden)

    Anatol GRAUR

    2017-06-01

    Full Text Available Tax planning is complex of measures,consisting in the reduction of tax payments under the law. Tax planning at the enterprise starts from the initial structuring of businesses and activities and can be carried out both at entity level (corporate and the individual (individual. Compared to tax evasion, tax planning is performed only under the law by avoiding taxes. Avoiding or reducing taxes is possible by organizing activities in such a way that the law allows reducing the tax base or tax rate. Optimization of tax payments is possible by organizing the work in such a way, so as the legislation avoids or reduces the tax base,tax rates and tax incentives application.

  14. Open source Modeling and optimization tools for Planning

    Energy Technology Data Exchange (ETDEWEB)

    Peles, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-02-10

    Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward to complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.

  15. Estimates of radiation over clouds and dust aerosols: Optimized number of terms in phase function expansion

    International Nuclear Information System (INIS)

    Ding Shouguo; Xie Yu; Yang Ping; Weng Fuzhong; Liu Quanhua; Baum, Bryan; Hu Yongxiang

    2009-01-01

    The bulk-scattering properties of dust aerosols and clouds are computed for the community radiative transfer model (CRTM) that is a flagship effort of the Joint Center for Satellite Data Assimilation (JCSDA). The delta-fit method is employed to truncate the forward peaks of the scattering phase functions and to compute the Legendre expansion coefficients for re-constructing the truncated phase function. Use of more terms in the expansion gives more accurate re-construction of the phase function, but the issue remains as to how many terms are necessary for different applications. To explore this issue further, the bidirectional reflectances associated with dust aerosols, water clouds, and ice clouds are simulated with various numbers of Legendre expansion terms. To have relative numerical errors smaller than 5%, the present analyses indicate that, in the visible spectrum, 16 Legendre polynomials should be used for dust aerosols, while 32 Legendre expansion terms should be used for both water and ice clouds. In the infrared spectrum, the brightness temperatures at the top of the atmosphere are computed by using the scattering properties of dust aerosols, water clouds and ice clouds. Although small differences of brightness temperatures compared with the counterparts computed with 4, 8, 128 expansion terms are observed at large viewing angles for each layer, it is shown that 4 terms of Legendre polynomials are sufficient in the radiative transfer computation at infrared wavelengths for practical applications.

  16. Functional avoidance of lung in plan optimization with an aperture-based inverse planning system

    International Nuclear Information System (INIS)

    St-Hilaire, Jason; Lavoie, Caroline; Dagnault, Anne; Beaulieu, Frederic; Morin, Francis; Beaulieu, Luc; Tremblay, Daniel

    2011-01-01

    Purpose: To implement SPECT-based optimization in an anatomy-based aperture inverse planning system for the functional avoidance of lung in thoracic irradiation. Material and methods: SPECT information has been introduced as a voxel-by-voxel modulation of lung importance factors proportionally to the local perfusion count. Fifteen cases of lung cancer have been retrospectively analyzed by generating angle-optimized non-coplanar plans, comparing a purely anatomical approach and our functional approach. Planning target volume coverage and lung sparing have been compared. Statistical significance was assessed by a Wilcoxon matched pairs test. Results: For similar target coverage, perfusion-weighted volume receiving 10 Gy was reduced by a median of 2.2% (p = 0.022) and mean perfusion-weighted lung dose, by a median of 0.9 Gy (p = 0.001). A separate analysis of patients with localized or non-uniform hypoperfusion could not show which would benefit more from SPECT-based treatment planning. Redirection of dose sometimes created overdosage regions in the target volume. Plans consisted of a similar number of segments and monitor units. Conclusions: Angle optimization and SPECT-based modulation of importance factors allowed for functional avoidance of the lung while preserving target coverage. The technique could be also applied to implement PET-based modulation inside the target volume, leading to a safer dose escalation.

  17. A key to success: optimizing the planning process

    Science.gov (United States)

    Turk, Huseyin; Karakaya, Kamil

    2014-05-01

    operation planning process is analyzed according to a comprehensive approach. The difficulties of planning are identified. Consequently, for optimizing a decisionmaking process of an air operation, a planning process is identified in a virtual command and control structure.

  18. The affordable care act and family planning services: the effect of optional medicaid expansion on safety net programs.

    Science.gov (United States)

    Lanese, Bethany G; Oglesby, Willie H

    2016-01-01

    Title X of the Public Health Service Act provides funding for a range of reproductive health services, with a priority given to low-income persons. Now that many of these services are provided to larger numbers of people with low-income since the passage of the Affordable Care Act and Medicaid expansion, questions remain on the continued need for the Title X program. The current project highlights the importance of these safety net programs. To help inform this policy issue, research was conducted to examine the revenue and service changes for Title X per state and compare those findings to the states' Medicaid expansion and demographics. The dataset include publicly available data from 2013 and 2014 Family Planning Annual Reports (FPAR). Paired samples differences of means t-tests were then used to compare the means of family planning participation rates for 2013 and 2014 across the different categories for Medicaid expansion states and non-expansion states. The ACA has had an impact on Title X services, but the link is not as direct as previously thought. The findings indicate that all states' Title X funded clinics lost revenue; however, expansion states fared better than non-expansion states. While the general statements from the FPAR National surveys certainly are supported in that Title X providers have decreased in number and scope of services, which has led to the decrease in total clients, these variations are not evenly applied across the states. The ACA has very likely had an impact on Title X services, but the link is not as obvious as previously thought. Title X funded clinics have helped increase access to health insurance at a greater rate in expansion states than non-expansion states. There was much concern from advocates that with the projected increased revenue from Medicaid and private insurance, that Title X programs could be deemed unnecessary. However, this revenue increase has yet to actually pan out. Title X still helps fill a much needed

  19. Aircraft path planning for optimal imaging using dynamic cost functions

    Science.gov (United States)

    Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

    2015-05-01

    Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

  20. Optimization of auxiliary basis sets for the LEDO expansion and a projection technique for LEDO-DFT.

    Science.gov (United States)

    Götz, Andreas W; Kollmar, Christian; Hess, Bernd A

    2005-09-01

    We present a systematic procedure for the optimization of the expansion basis for the limited expansion of diatomic overlap density functional theory (LEDO-DFT) and report on optimized auxiliary orbitals for the Ahlrichs split valence plus polarization basis set (SVP) for the elements H, Li--F, and Na--Cl. A new method to deal with near-linear dependences in the LEDO expansion basis is introduced, which greatly reduces the computational effort of LEDO-DFT calculations. Numerical results for a test set of small molecules demonstrate the accuracy of electronic energies, structural parameters, dipole moments, and harmonic frequencies. For larger molecular systems the numerical errors introduced by the LEDO approximation can lead to an uncontrollable behavior of the self-consistent field (SCF) process. A projection technique suggested by Löwdin is presented in the framework of LEDO-DFT, which guarantees for SCF convergence. Numerical results on some critical test molecules suggest the general applicability of the auxiliary orbitals presented in combination with this projection technique. Timing results indicate that LEDO-DFT is competitive with conventional density fitting methods. (c) 2005 Wiley Periodicals, Inc.

  1. Aerodynamic optimization of wind turbine rotors using a blade element momentum method with corrections for wake rotation and expansion

    DEFF Research Database (Denmark)

    Døssing, Mads; Aagaard Madsen, Helge; Bak, Christian

    2012-01-01

    The blade element momentum (BEM) method is widely used for calculating the quasi-steady aerodynamics of horizontal axis wind turbines. Recently, the BEM method has been expanded to include corrections for wake expansion and the pressure due to wake rotation (), and more accurate solutions can now...... by the positive effect of wake rotation, which locally causes the efficiency to exceed the Betz limit. Wake expansion has a negative effect, which is most important at high tip speed ratios. It was further found that by using , it is possible to obtain a 5% reduction in flap bending moment when compared with BEM....... In short, allows fast aerodynamic calculations and optimizations with a much higher degree of accuracy than the traditional BEM model. Copyright © 2011 John Wiley & Sons, Ltd....

  2. Autonomous guided vehicles methods and models for optimal path planning

    CERN Document Server

    Fazlollahtabar, Hamed

    2015-01-01

      This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...

  3. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  4. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    Science.gov (United States)

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  5. Optimal Diet Planning for Eczema Patient Using Integer Programming

    Science.gov (United States)

    Zhen Sheng, Low; Sufahani, Suliadi

    2018-04-01

    Human diet planning is conducted by choosing appropriate food items that fulfill the nutritional requirements into the diet formulation. This paper discusses the application of integer programming to build the mathematical model of diet planning for eczema patients. The model developed is used to solve the diet problem of eczema patients from young age group. The integer programming is a scientific approach to select suitable food items, which seeks to minimize the costs, under conditions of meeting desired nutrient quantities, avoiding food allergens and getting certain foods into the diet that brings relief to the eczema conditions. This paper illustrates that the integer programming approach able to produce the optimal and feasible solution to deal with the diet problem of eczema patient.

  6. A Generalized Orienteering Problem for Optimal Search and Interdiction Planning

    Science.gov (United States)

    2013-09-01

    proposed for the TOP. Boussier et al. (2007) presents a branch-and- price algorithm that relies on a pricing step within the column generation phase...dominates in all metric categories and B&B appears to be the least favorable. We use performance proles ( Dolan and Moré 2002) as a method for comparing...exceeded, with greater computing power it may be possible to obtain the optimal solution in a period of time that can support a 24-hour planning

  7. A complex of optimization problems in planning for the development of mining operations in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Todorov, A K; Arnaudov, B K; Brankova, B A; Gyuleva, B I; Zakhariyev, G K

    1977-01-01

    The system for planning for the development of coal mines is a complex of interrelated plan optimization, plan calculation and supporting (accounting-analytical and standards) tasks. An important point in this complex is held by the plan optimization tasks. The questions about the synthesis and the structural peculiarities of the system, the essence and machine realization of the tasks are examined.

  8. Decenal plan of electric energy expansion - 2006-2015; Plano decenal de expansao de energia eletrica - 2006-2015

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    This report is divided into seven chapters and presents: 1) Introduction - a brief description of the institutional context of the study and the decenal planning role in this context; 2) electric power market - the evolution of market and economy conjuncture of electric power and the basic premises for the market projections, including the considered macroeconomic scenery description; 3) electric power generation - considered premises, methodology and criteria for the formulation and adjustment of generation expansion alternatives of electric power; 4) electric power transmission - main aspects which guided the evolution of the interlinked system reference configuration in the decenal period and a description of the main result of transmission system expansion analysis, consolidated by SIN geoelectric region and by each state of these regions; 5) socioenvironmental analysis - adopted methodology and the results of the socioenvironmental analysis for the foreseen business in the decenal horizon; 6) expansion indicators of the electric system - synthesizes the main indicators referring to the decenal period as far the market evolution, generation expansion and transmission is concerned; 7)bibliographic references.

  9. Optimal planning for the sustainable utilization of municipal solid waste

    Energy Technology Data Exchange (ETDEWEB)

    Santibañez-Aguilar, José Ezequiel [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Ponce-Ortega, José María, E-mail: jmponce@umich.mx [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Betzabe González-Campos, J. [Institute of Chemical and Biological Researches, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); Serna-González, Medardo [Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán 58060 (Mexico); El-Halwagi, Mahmoud M. [Chemical Engineering Department, Texas A and M University, College Station, TX 77843 (United States); Adjunct Faculty at the Chemical and Materials Engineering Department, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589 (Saudi Arabia)

    2013-12-15

    Highlights: • An optimization approach for the sustainable management of municipal solid waste is proposed. • The proposed model optimizes the entire supply chain network of a distributed system. • A case study for the sustainable waste management in the central-west part of Mexico is presented. • Results shows different interesting solutions for the case study presented. - Abstract: The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits.

  10. Optimal planning for the sustainable utilization of municipal solid waste

    International Nuclear Information System (INIS)

    Santibañez-Aguilar, José Ezequiel; Ponce-Ortega, José María; Betzabe González-Campos, J.; Serna-González, Medardo; El-Halwagi, Mahmoud M.

    2013-01-01

    Highlights: • An optimization approach for the sustainable management of municipal solid waste is proposed. • The proposed model optimizes the entire supply chain network of a distributed system. • A case study for the sustainable waste management in the central-west part of Mexico is presented. • Results shows different interesting solutions for the case study presented. - Abstract: The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits

  11. Vanpool trip planning based on evolutionary multiple objective optimization

    Science.gov (United States)

    Zhao, Ming; Yang, Disheng; Feng, Shibing; Liu, Hengchang

    2017-08-01

    Carpool and vanpool draw a lot of researchers’ attention, which is the emphasis of this paper. A concrete vanpool operation definition is given, based on the given definition, this paper tackles vanpool operation optimization using user experience decline index(UEDI). This paper is focused on making each user having identical UEDI and the system having minimum sum of all users’ UEDI. Three contributions are made, the first contribution is a vanpool operation scheme diagram, each component of the scheme is explained in detail. The second contribution is getting all customer’s UEDI as a set, standard deviation and sum of all users’ UEDI set are used as objectives in multiple objective optimization to decide trip start address, trip start time and trip destination address. The third contribution is a trip planning algorithm, which tries to minimize the sum of all users’ UEDI. Geographical distribution of the charging stations and utilization rate of the charging stations are considered in the trip planning process.

  12. Optimal planning for the sustainable utilization of municipal solid waste.

    Science.gov (United States)

    Santibañez-Aguilar, José Ezequiel; Ponce-Ortega, José María; Betzabe González-Campos, J; Serna-González, Medardo; El-Halwagi, Mahmoud M

    2013-12-01

    The increasing generation of municipal solid waste (MSW) is a major problem particularly for large urban areas with insufficient landfill capacities and inefficient waste management systems. Several options associated to the supply chain for implementing a MSW management system are available, however to determine the optimal solution several technical, economic, environmental and social aspects must be considered. Therefore, this paper proposes a mathematical programming model for the optimal planning of the supply chain associated to the MSW management system to maximize the economic benefit while accounting for technical and environmental issues. The optimization model simultaneously selects the processing technologies and their location, the distribution of wastes from cities as well as the distribution of products to markets. The problem was formulated as a multi-objective mixed-integer linear programing problem to maximize the profit of the supply chain and the amount of recycled wastes, where the results are showed through Pareto curves that tradeoff economic and environmental aspects. The proposed approach is applied to a case study for the west-central part of Mexico to consider the integration of MSW from several cities to yield useful products. The results show that an integrated utilization of MSW can provide economic, environmental and social benefits. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Optimal planning in a developing industrial microgrid with sensitive loads

    Directory of Open Access Journals (Sweden)

    M. Naderi

    2017-11-01

    Full Text Available Computer numerical control (CNC machines are known as sensitive loads in industrial estates. These machines require reliable and qualified electricity in their often long work periods. Supplying these loads with distributed energy resources (DERs in a microgrid (MG can be done as an appropriate solution. The aim of this paper is to analyze the implementation potential of a real and developing MG in Shad-Abad industrial estate, Tehran, Iran. Three MG planning objectives are considered including assurance of sustainable and secure operation of CNC machines as sensitive loads, minimizing the costs of MG construction and operation, and using available capacities to penetrate the highest possible renewable energy sources (RESs which subsequently results in decreasing the air pollutants specially carbon dioxide (CO2. The HOMER (hybrid optimization model for electric renewable software is used to specify the technical feasibility of MG planning and to select the best plan economically and environmentally. Different scenarios are considered in this regard to determine suitable capacity of production participants, and to assess the MG indices such as the reliability.

  14. Optimizing the Long-Term Capacity Expansion and Protection of Iraqi Oil Infrastructure

    National Research Council Canada - National Science Library

    Brown, Patrick S

    2005-01-01

    This thesis introduces a tri-level defender-attacker-defender optimization model that prescribes how Iraq's oil infrastructure can, over time, be expanded, protected, and operated, even in the face of insurgent attacks...

  15. Preparatory Work for a Scenario-Based Electricity Expansion Plan for North Korea after Hypothetical Reunification using WASP-IV

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young Joo; Chang, Choong Koo [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2014-10-15

    It is noteworthy that North Korean government itself has demanded other parties' cooperation in the field of power sector as the top priority to deal with North Korean own economic issues. In this light, the researcher consider that how to build power capacity in North Korean area after reunification needs to be studied with priority. A scenario-based approach is being adopted, and three scenarios are proposed: Scenario increasing capacity at 2.4% annual rate, Imitating South Korean electricity expansion history, and reaching 80% of South Korean Annual Peak Load in 35 years. In order to carry out the research, WASP-IV (Wien Automation System Planning-IV) code developed by IAEA is, with reasonable assumptions, being executed. Annual Peak Load prediction for each scenario, load duration curve, and existing power generating facilities in North Korea are presented herein. This research is being conducted as a preparatory work for the further study. IAEA's WASP-IV is adopted for a scenario-based electricity expansion plan for North Korea after hypothetical reunification between Koreas. Input data including Annual Peak Load, load duration curve, and existing facilities are built and presented. Additional future research includes inputting candidate plants data, cost data such as construction period, operation and maintenance costs, and fuel costs, as well as decommissioning of aged power plants in North Korea to complete WASP-IV execution. Assuming reunification, electricity expansion plan would need to integrate North and South Koreas demands and facilities. However, this research narrows down its scope to North Korean demand and facilities only. Such integrated simulation could be the topic for the later research. This work was supported by the 2014 Research Fund of the KINGS.

  16. Preparatory Work for a Scenario-Based Electricity Expansion Plan for North Korea after Hypothetical Reunification using WASP-IV

    International Nuclear Information System (INIS)

    Kim, Young Joo; Chang, Choong Koo

    2014-01-01

    It is noteworthy that North Korean government itself has demanded other parties' cooperation in the field of power sector as the top priority to deal with North Korean own economic issues. In this light, the researcher consider that how to build power capacity in North Korean area after reunification needs to be studied with priority. A scenario-based approach is being adopted, and three scenarios are proposed: Scenario increasing capacity at 2.4% annual rate, Imitating South Korean electricity expansion history, and reaching 80% of South Korean Annual Peak Load in 35 years. In order to carry out the research, WASP-IV (Wien Automation System Planning-IV) code developed by IAEA is, with reasonable assumptions, being executed. Annual Peak Load prediction for each scenario, load duration curve, and existing power generating facilities in North Korea are presented herein. This research is being conducted as a preparatory work for the further study. IAEA's WASP-IV is adopted for a scenario-based electricity expansion plan for North Korea after hypothetical reunification between Koreas. Input data including Annual Peak Load, load duration curve, and existing facilities are built and presented. Additional future research includes inputting candidate plants data, cost data such as construction period, operation and maintenance costs, and fuel costs, as well as decommissioning of aged power plants in North Korea to complete WASP-IV execution. Assuming reunification, electricity expansion plan would need to integrate North and South Koreas demands and facilities. However, this research narrows down its scope to North Korean demand and facilities only. Such integrated simulation could be the topic for the later research. This work was supported by the 2014 Research Fund of the KINGS

  17. Evaluating Clonal Expansion of HIV-Infected Cells: Optimization of PCR Strategies to Predict Clonality

    Science.gov (United States)

    Laskey, Sarah B.; Pohlmeyer, Christopher W.; Bruner, Katherine M.; Siliciano, Robert F.

    2016-01-01

    In HIV-infected individuals receiving suppressive antiretroviral therapy, the virus persists indefinitely in a reservoir of latently infected cells. The proliferation of these cells may contribute to the stability of the reservoir and thus to the lifelong persistence of HIV-1 in infected individuals. Because the HIV-1 replication process is highly error-prone, the detection of identical viral genomes in distinct host cells provides evidence for the clonal expansion of infected cells. We evaluated alignments of unique, near-full-length HIV-1 sequences to determine the relationship between clonality in a short region and clonality in the full genome. Although it is common to amplify and sequence short, subgenomic regions of the viral genome for phylogenetic analysis, we show that sequence identity of these amplicons does not guarantee clonality across the full viral genome. We show that although longer amplicons capture more diversity, no subgenomic region can recapitulate the diversity of full viral genomes. Consequently, some identical subgenomic amplicons should be expected even from the analysis of completely unique viral genomes, and the presence of identical amplicons alone is not proof of clonally expanded HIV-1. We present a method for evaluating evidence of clonal expansion in the context of these findings. PMID:27494508

  18. Evaluating Clonal Expansion of HIV-Infected Cells: Optimization of PCR Strategies to Predict Clonality.

    Directory of Open Access Journals (Sweden)

    Sarah B Laskey

    2016-08-01

    Full Text Available In HIV-infected individuals receiving suppressive antiretroviral therapy, the virus persists indefinitely in a reservoir of latently infected cells. The proliferation of these cells may contribute to the stability of the reservoir and thus to the lifelong persistence of HIV-1 in infected individuals. Because the HIV-1 replication process is highly error-prone, the detection of identical viral genomes in distinct host cells provides evidence for the clonal expansion of infected cells. We evaluated alignments of unique, near-full-length HIV-1 sequences to determine the relationship between clonality in a short region and clonality in the full genome. Although it is common to amplify and sequence short, subgenomic regions of the viral genome for phylogenetic analysis, we show that sequence identity of these amplicons does not guarantee clonality across the full viral genome. We show that although longer amplicons capture more diversity, no subgenomic region can recapitulate the diversity of full viral genomes. Consequently, some identical subgenomic amplicons should be expected even from the analysis of completely unique viral genomes, and the presence of identical amplicons alone is not proof of clonally expanded HIV-1. We present a method for evaluating evidence of clonal expansion in the context of these findings.

  19. Extended gamma sources modelling using multipole expansion: Application to the Tunisian gamma source load planning

    International Nuclear Information System (INIS)

    Loussaief, Abdelkader

    2007-01-01

    In this work we extend the use of multipole moments expansion to the case of inner radiation fields. A series expansion of the photon flux was established. The main advantage of this approach is that it offers the opportunity to treat both inner and external radiation field cases. We determined the expression of the inner multipole moments in both spherical harmonics and in cartesian coordinates. As an application we applied the analytical model to a radiation facility used for small target irradiation. Theoretical, experimental and simulation studies were performed, in air and in a product, and good agreement was reached.Conventional dose distribution study for gamma irradiation facility involves the use of isodose maps. The establishment of these maps requires the measurement of the absorbed dose in many points, which makes the task expensive experimentally and very long by simulation. However, a lack of points of measurement can distort the dose distribution cartography. To overcome these problems, we present in this paper a mathematical method to describe the dose distribution in air. This method is based on the multipole expansion in spherical harmonics of the photon flux emitted by the gamma source. The determination of the multipole coefficients of this development allows the modeling of the radiation field around the gamma source. (Author)

  20. Reduction of CO{sub 2} emissions by means of expansion, information technological cross-linking and grid optimization of plans for the utilization of decentral, fluctuating and renewable energy in Germany; CO{sub 2}-Emissionsminderung durch Ausbau, informationstechnische Vernetzung und Netzoptimierung von Anlagen dezentraler, fluktuierender und erneuerbarer Energienutzung in Deutschland

    Energy Technology Data Exchange (ETDEWEB)

    Lanz, Marco; Fricke, Barbara; Anthrakidis, Anette [FH Aachen (DE). Solar-Institut Juelich

    2011-11-15

    in the grid and energy system; and - The potentials of possible CO{sub 2} emission abatements brought about by the interweaving and flexibilisation on the part of consumers and producers, on the one hand, and promotion of the expansion of decentralised power plant capacities on the other hand. (orig.)

  1. Fast Generation of Near-Optimal Plans for Eco-Efficient Stowage of Large Container Vessels

    DEFF Research Database (Denmark)

    Pacino, Dario; Delgado, Alberto; Jensen, Rune Møller

    2011-01-01

    Eco-efficient stowage plans that are both competitive and sustainable have become a priority for the shipping industry. Stowage planning is NP-hard and is a challenging optimization problem in practice. We propose a new 2-phase approach that generates near-optimal stowage plans and fulfills indus...

  2. Optimal inspection planning for onshore pipelines subject to external corrosion

    International Nuclear Information System (INIS)

    Gomes, Wellison J.S.; Beck, André T.; Haukaas, Terje

    2013-01-01

    Continuous operation of pipeline systems involves significant expenditures in inspection and maintenance activities. The cost-effective safety management of such systems involves allocating the optimal amount of resources to inspection and maintenance activities, in order to control risks (expected costs of failure). In this context, this article addresses the optimal inspection planning for onshore pipelines subject to external corrosion. The investigation addresses a challenging problem of practical relevance, and strives for using the best available models to describe random corrosion growth and the relevant limit state functions. A single pipeline segment is considered in this paper. Expected numbers of failures and repairs are evaluated by Monte Carlo sampling, and a novel procedure is employed to evaluate sensitivities of the objective function with respect to design parameters. This procedure is shown to be accurate and more efficient than finite differences. The optimum inspection interval is found for an example problem, and the robustness of this optimum to the assumed inspection and failure costs is investigated. It is shown that optimum total expected costs found herein are not highly sensitive to the assumed costs of inspection and failure. -- Highlights: • Inspection, repair and failure costs of pipeline systems considered. • Optimum inspection schedule (OIS) obtained by minimizing total expected life-cycle costs. • Robustness of OIS evaluated w.r.t. estimated costs of inspection and failure. • Accurate non-conservative models of corrosion growth employed

  3. Optimal Control Approaches to the Aggregate Production Planning Problem

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2015-12-01

    Full Text Available In the area of production planning and control, the aggregate production planning (APP problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.

  4. Phase shift analysis of hyperon-nucleon elastic scattering using optimized polynomial expansion techniques

    International Nuclear Information System (INIS)

    Mohanty, S.; Deo, B.B.; Mohapatra, J.K.

    1986-01-01

    A relatively stable method of phase shift analysis of hyperon-nucleon scattering is proposed and applied to Σ + p and Λp scattering. The analytic cut t-planes of analyticity of the helicity amplitudes are mapped into the interior of unifocal ellipses. The helicity amplitudes are then expressed as accelerated convergent expansions in the mapped variable. A definite economy is observed in the number of free parameters for fixed energy phase shift analysis of Σ + p and Λp scattering at 40 and 100 MeV and 100 MeV respectively. Twenty six more phase shifts and coupling parameters corresponding to higher J values are also predicted. (author)

  5. Genetic algorithm optimization for dynamic construction site layout planning

    Directory of Open Access Journals (Sweden)

    Farmakis Panagiotis M.

    2018-02-01

    Full Text Available The dynamic construction site layout planning (DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indi­cate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process.

  6. Geometry Optimization of an Overtopping Wave Energy Device Implemented into the New Breakwater of the Hanstholm Port Expansion

    DEFF Research Database (Denmark)

    Margheritini, Lucia; Stratigaki, Vasiliki; Troch, Peter

    2012-01-01

    breakwater is 1.5 km and the water depth ranges approximately from 8.0 m up to 14 m with localized influences on the wave climate. The study is conducted numerically in order to present the expected power production and overall performance of the SSG breakwater in Hanstholm. The price par kWh is also......The study presented here describes the geometry optimization of the Sea wave Slot cone Generator (SSG) overtopping wave energy converter as part of the feasibility study for the implementation of the device in the development plan of Hanstholm harbour in Denmark. The total length of the new planned...

  7. A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Li, Nan; Long, Troy; Romeijn, H. Edwin; Tian, Zhen; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment

  8. Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

    Science.gov (United States)

    Hoffmann, Aswin L.; Siem, Alex Y. D.; den Hertog, Dick; Kaanders, Johannes H. A. M.; Huizenga, Henk

    2006-12-01

    In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

  9. Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

    International Nuclear Information System (INIS)

    Hoffmann, Aswin L; Siem, Alex Y D; Hertog, Dick den; Kaanders, Johannes H A M; Huizenga, Henk

    2006-01-01

    In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning

  10. Energy Efficient Pico Cell Range Expansion and Density Joint Optimization for Heterogeneous Networks with eICIC

    Directory of Open Access Journals (Sweden)

    Yanzan Sun

    2018-03-01

    Full Text Available Heterogeneous networks, constituted by conventional macro cells and overlaying pico cells, have been deemed a promising paradigm to support the deluge of data traffic with higher spectral efficiency and Energy Efficiency (EE. In order to deploy pico cells in reality, the density of Pico Base Stations (PBSs and the pico Cell Range Expansion (CRE are two important factors for the network spectral efficiency as well as EE improvement. However, associated with the range and density evolution, the inter-tier interference within the heterogeneous architecture will be challenging, and the time domain Enhanced Inter-cell Interference Coordination (eICIC technique becomes necessary. Aiming to improve the network EE, the above factors are jointly considered in this paper. More specifically, we first derive the closed-form expression of the network EE as a function of the density of PBSs and pico CRE bias based on stochastic geometry theory, followed by a linear search algorithm to optimize the pico CRE bias and PBS density, respectively. Moreover, in order to realize the pico CRE bias and PBS density joint optimization, a heuristic algorithm is proposed to achieve the network EE maximization. Numerical simulations show that our proposed pico CRE bias and PBS density joint optimization algorithm can improve the network EE significantly with low computational complexity.

  11. Optimal electricity generation system expansion and nuclear power option in Belarus

    International Nuclear Information System (INIS)

    Yakushau, A.; Mikhalevich, A.

    2000-01-01

    After having declared independence, the Republic of Belarus was forced to import 90% of fuel consumed and 25% of electricity. The deficit of peak electric capacity reached 40%. The imported fuel covers the last years because the drop in the production reduced the energy consumption in the Republic but not the needs of the energy sector. Annual payments for imported fuel and electricity are equal to the sum of an annual state budget of Belarus (about 1.5 billion USD) and current debts were not lower 300 million. Comparative analysis of the different scenarios of the electricity generation system expansion showed that an optimum way for electricity generation is installation of the combine cycle units and construction nuclear power plants. The results of the study also showed that the option based on replacement of deficit of the electricity generation by the way of the construction combine cycle units with capacities 450 MW turned out to be the best solution among non nuclear options. (author)

  12. Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

    Science.gov (United States)

    Sherry, Lance; Ferguson, John; Hoffman, Karla; Donohue, George; Beradino, Frank

    2012-01-01

    This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

  13. Long-term power generation expansion planning with short-term demand response: Model, algorithms, implementation, and electricity policies

    Science.gov (United States)

    Lohmann, Timo

    Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the

  14. Mathematical optimization for planning and design of cycle paths

    Energy Technology Data Exchange (ETDEWEB)

    LiÑan Ruiz, R.J.; Perez Aracil, J.; Cabrera Cañizares, V.

    2016-07-01

    The daily need for citizens to move for different activities, whatever its nature, has been greatly affected by the changes. The advantages resulting from the inclusion of the bicycle as a mode of transport and the proliferation of its use among citizens are numerous and extend both in the field of urban mobility and sustainable development.Currently, there are a number of programs for the implementation, promotion or increased public participation related to cycling in cities. But ultimately, each and every one of these initiatives have the same goal, to create a mesh of effective, useful and cycling trails that allow the use of bicycles in preferred routes with high guarantees of security, incorporating bicycle model intermodal urban transport.With the gradual implementation of bike lanes, many people have begun to use them to get around the city. But everything again needs a period of adaptation, and the reality is that the road network for these vehicles is full of obstacles to the rider. The current situation has led to the proposal that many kilometers of cycle paths needed to supply the demand of this mode of transport and, if implemented and planned are correct and sufficient.This paper presents a mathematical programming model for optimal design of a network for cyclists is presented. Specifically, the model determines a network of bicycle infrastructure, appropriate to the characteristics of a network of existing roads.As an application of the proposed model, the result of these experiments give a number of useful conclusions for planning and designing networks of cycle paths from a social perspective, applied to the case in the city of Malaga. (Author)

  15. Performance of Optimization Heuristics for the Operational Planning of Multi-energy Storage Systems

    Science.gov (United States)

    Haas, J.; Schradi, J.; Nowak, W.

    2016-12-01

    In the transition to low-carbon energy sources, energy storage systems (ESS) will play an increasingly important role. Particularly in the context of solar power challenges (variability, uncertainty), ESS can provide valuable services: energy shifting, ramping, robustness against forecast errors, frequency support, etc. However, these qualities are rarely modelled in the operational planning of power systems because of the involved computational burden, especially when multiple ESS technologies are involved. This work assesses two optimization heuristics for speeding up the optimal operation problem. It compares their accuracy (in terms of costs) and speed against a reference solution. The first heuristic (H1) is based on a merit order. Here, the ESS are sorted from lower to higher operational costs (including cycling costs). For each time step, the cheapest available ESS is used first, followed by the second one and so on, until matching the net load (demand minus available renewable generation). The second heuristic (H2) uses the Fourier transform to detect the main frequencies that compose the net load. A specific ESS is assigned to each frequency range, aiming to smoothen the net load. Finally, the reference solution is obtained with a mixed integer linear program (MILP). H1, H2 and MILP are subject to technical constraints (energy/power balance, ramping rates, on/off states...). Costs due to operation, replacement (cycling) and unserved energy are considered. Four typical days of a system with a high share of solar energy were used in several test cases, varying the resolution from one second to fifteen minutes. H1 and H2 achieve accuracies of about 90% and 95% in average, and speed-up times of two to three and one to two orders of magnitude, respectively. The use of the heuristics looks promising in the context of planning the expansion of power systems, especially when their loss of accuracy is outweighed by solar or wind forecast errors.

  16. Microscopically based energy density functionals for nuclei using the density matrix expansion. II. Full optimization and validation

    Science.gov (United States)

    Navarro Pérez, R.; Schunck, N.; Dyhdalo, A.; Furnstahl, R. J.; Bogner, S. K.

    2018-05-01

    Background: Energy density functional methods provide a generic framework to compute properties of atomic nuclei starting from models of nuclear potentials and the rules of quantum mechanics. Until now, the overwhelming majority of functionals have been constructed either from empirical nuclear potentials such as the Skyrme or Gogny forces, or from systematic gradient-like expansions in the spirit of the density functional theory for atoms. Purpose: We seek to obtain a usable form of the nuclear energy density functional that is rooted in the modern theory of nuclear forces. We thus consider a functional obtained from the density matrix expansion of local nuclear potentials from chiral effective field theory. We propose a parametrization of this functional carefully calibrated and validated on selected ground-state properties that is suitable for large-scale calculations of nuclear properties. Methods: Our energy functional comprises two main components. The first component is a non-local functional of the density and corresponds to the direct part (Hartree term) of the expectation value of local chiral potentials on a Slater determinant. Contributions to the mean field and the energy of this term are computed by expanding the spatial, finite-range components of the chiral potential onto Gaussian functions. The second component is a local functional of the density and is obtained by applying the density matrix expansion to the exchange part (Fock term) of the expectation value of the local chiral potential. We apply the UNEDF2 optimization protocol to determine the coupling constants of this energy functional. Results: We obtain a set of microscopically constrained functionals for local chiral potentials from leading order up to next-to-next-to-leading order with and without three-body forces and contributions from Δ excitations. These functionals are validated on the calculation of nuclear and neutron matter, nuclear mass tables, single-particle shell structure

  17. Expansion planning of the electric systems in a competitive environment context; O planejamento da expansao dos sistemas eletricos no contexto de um ambiente competitivo

    Energy Technology Data Exchange (ETDEWEB)

    Haffner, Sergio Luis

    2000-07-01

    An integrated dynamic expansion planning model of electric energy systems model is proposed. Such model can be used by an independent structure of planning, compatible with the current competitive environment of the electric industry. The investments in generation and transmission are obtained simultaneously, taking into account a long term planning horizon that is split in multiple stages. In the proposed model, the entity responsible for the expansion planning, the Independent Expansion Planner, divulges the indicative expansion plan and other information that will be used by the sector agents to guide its investments in that area. Three network models are used (transport, DC load flow and hybrid transport-DC) in an hierarchical algorithm that uses the Benders decomposition to solve the problem of capacity expansion, considering the investment and operation costs. The original problem is separated in a master subproblem (investment) and several slave subproblems (operation). Each stage is represented by an operation subproblem and the master subproblem is solved by an specialized branch-and-bound algorithm. The operation subproblems (LP problems) are solved through the MINOS package. Strategies to improve the performance of the described algorithm are discussed and presented. The efficiency of those strategies is shown through tests using theoretical and realistic electric systems. The developed branch-and-bound algorithm and the selection techniques employed are described in details and illustrated through examples. It is presented, also, the Independent Planner role and its relevance in the current context of the national electric industry is pointed out. (author)

  18. Master plan envisions multi-billion-dollar expansion of Vietnam's electricity monopoly

    International Nuclear Information System (INIS)

    2001-12-01

    Massive investment in Vietnam's electricity monopoly by Western aid and export credit agencies form part of the ten-year master plan developed for Vietnam. Central planning and political patronage, instead of market assessments and customer choice form the basis for monopoly investments in a centralized grid linking big hydro, gas, coal, and nuclear power projects. Western aid agencies might effectively crowd out viable private-sector energy investments by financing power projects considered too large and risky by the private sector. These investments by Western aid agencies would assist in winning contracts for favoured exporters of engineering services and equipment. It would be a breeding ground for corruption in Vietnam if market discipline, public oversight, and enforceable property rights are not present in the face of power sector aid. There is a real possibility that damages to the environment could result from electricity investments, and some communities might be victimized, electricity costs might increase, the indebtedness level of the population might increase

  19. Long vigil in Athabasca oil sands culminates in rapid expansion plans

    Energy Technology Data Exchange (ETDEWEB)

    1974-05-01

    Great Canadian Oil Sands Ltd. needs to earn $40 million or more per year to get a reasonable return on the investment, vice president and general manager R.D. Humphreys told delegates at the Petroleum Accountants Society of W. Canada annual conference at Jasper Park Lodge. The conference then was ''the Alberta Oil Sands.'' Sun Oil Co. has taken no return yet, but has paid off the loans and taken shares in return so it owns nearly all the equity capital. The operation is not really breaking even at present, but should improve because GCOS is getting the full effect of the oil price increase under the original royalty agreement with the Alberta government. It is hoped that this will enable the company to recoup an accumulated deficit of more than $90 million. Money is the biggest problem for the current expansion designed to raise production to the authorized 65,000 bpd. Manpower is second and delivery of materials third. There is a lead time of 15 to 18 mo. on critical materials. Over the long term, tailings disposal is the greatest single problem facing all oil sands operators.

  20. Multi-Criteria Analyses of Urban Planning for City Expansion: A Case Study of Zamora, Spain

    Directory of Open Access Journals (Sweden)

    Marco Criado

    2017-10-01

    Full Text Available This study has established a methodology to determine the most environmentally suitable area for the expansion of Zamora (Spain using geographic information system (GIS technology. The objective was to develop a GIS-based methodology for the identification of urban peripheral areas that are suitable for the accommodation of new buildings and services, that are compliant with environmental criteria, and that guarantee an adequate quality of life for the future population such that extra construction costs are avoided. The methodological core is based on two multi-criteria analyses (MCAs: MCA-1 determines areas suitable for building—the most environmentally sustainable areas that do not present risks or discomforts to the population—by analyzing the restrictive factors; MCA-2 takes the sectors that received a favorable evaluation in MCA-1, determines which of those have a lower economic overhead for construction, and analyzes the different conditioning criteria related to their pre-existing infrastructures. Finally, the location of the sectors is determined by a decision factor that satisfies some strategic need of the municipality.

  1. A fast optimization algorithm for multicriteria intensity modulated proton therapy planning

    International Nuclear Information System (INIS)

    Chen Wei; Craft, David; Madden, Thomas M.; Zhang, Kewu; Kooy, Hanne M.; Herman, Gabor T.

    2010-01-01

    Purpose: To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. Methods: The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. Results: The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK's interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. Conclusions: The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

  2. A fast optimization algorithm for multicriteria intensity modulated proton therapy planning.

    Science.gov (United States)

    Chen, Wei; Craft, David; Madden, Thomas M; Zhang, Kewu; Kooy, Hanne M; Herman, Gabor T

    2010-09-01

    To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK'S interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

  3. Optimization of the production plan and risk control in Third Qinshan Nuclear Power Co.,Ltd

    International Nuclear Information System (INIS)

    Zhou Jun

    2009-01-01

    Some optimized and improved measures have been taken in Third Qinshan Nuclear Power Co., Ltd. (TQNPC) to optimize the routine production plan management, strengthen the maintenance work risk analysis, and improve the plan execution capability. Which involve unified management of generation, refueling, periodic test and maintenance plans; simplifying the defect scale and reducing the intermediate link of defect treatment; intensifying the appraisal on plan execution and adopting star performance evaluation and merit rating measures. In this paper, the above-mentioned improvement and optimization are introduced comprehensively and systematically. (authors)

  4. Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dae Sup; Yoon, In Ha; Lee, Woo Seok; Baek, Geum Mun [Dept. of Radiation Oncology, Asan Medical Center, Seoul (Korea, Republic of)

    2012-09-15

    Analyze the Effectiveness of Radiation Treatment Planning by dose calculation and optimization algorithm, apply consideration of actual treatment planning, and then suggest the best way to treatment planning protocol. The treatment planning system use Eclipse 10.0. (Varian, USA). PBC (Pencil Beam Convolution) and AAA (Anisotropic Analytical Algorithm) Apply to Dose calculation, DVO (Dose Volume Optimizer 10.0.28) used for optimized algorithm of Intensity Modulated Radiation Therapy (IMRT), PRO II (Progressive Resolution Optimizer V 8.9.17) and PRO III (Progressive Resolution Optimizer V 10.0.28) used for optimized algorithm of VAMT. A phantom for experiment virtually created at treatment planning system, 30x30x30 cm sized, homogeneous density (HU: 0) and heterogeneous density that inserted air assumed material (HU: -1,000). Apply to clinical treatment planning on the basis of general treatment planning feature analyzed with Phantom planning. In homogeneous density phantom, PBC and AAA show 65.2% PDD (6 MV, 10 cm) both, In heterogeneous density phantom, also show similar PDD value before meet with low density material, but they show different dose curve in air territory, PDD 10 cm showed 75%, 73% each after penetrate phantom. 3D treatment plan in same MU, AAA treatment planning shows low dose at Lung included area. 2D POP treatment plan with 15 MV of cervical vertebral region include trachea and lung area, Conformity Index (ICRU 62) is 0.95 in PBC calculation and 0.93 in AAA. DVO DVH and Dose calculation DVH are showed equal value in IMRT treatment plan. But AAA calculation shows lack of dose compared with DVO result which is satisfactory condition. Optimizing VMAT treatment plans using PRO II obtained results were satisfactory, but lower density area showed lack of dose in dose calculations. PRO III, but optimizing the dose calculation results were similar with optimized the same conditions once more. In this study, do not judge the rightness of the dose

  5. Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

    International Nuclear Information System (INIS)

    Kim, Dae Sup; Yoon, In Ha; Lee, Woo Seok; Baek, Geum Mun

    2012-01-01

    Analyze the Effectiveness of Radiation Treatment Planning by dose calculation and optimization algorithm, apply consideration of actual treatment planning, and then suggest the best way to treatment planning protocol. The treatment planning system use Eclipse 10.0. (Varian, USA). PBC (Pencil Beam Convolution) and AAA (Anisotropic Analytical Algorithm) Apply to Dose calculation, DVO (Dose Volume Optimizer 10.0.28) used for optimized algorithm of Intensity Modulated Radiation Therapy (IMRT), PRO II (Progressive Resolution Optimizer V 8.9.17) and PRO III (Progressive Resolution Optimizer V 10.0.28) used for optimized algorithm of VAMT. A phantom for experiment virtually created at treatment planning system, 30x30x30 cm sized, homogeneous density (HU: 0) and heterogeneous density that inserted air assumed material (HU: -1,000). Apply to clinical treatment planning on the basis of general treatment planning feature analyzed with Phantom planning. In homogeneous density phantom, PBC and AAA show 65.2% PDD (6 MV, 10 cm) both, In heterogeneous density phantom, also show similar PDD value before meet with low density material, but they show different dose curve in air territory, PDD 10 cm showed 75%, 73% each after penetrate phantom. 3D treatment plan in same MU, AAA treatment planning shows low dose at Lung included area. 2D POP treatment plan with 15 MV of cervical vertebral region include trachea and lung area, Conformity Index (ICRU 62) is 0.95 in PBC calculation and 0.93 in AAA. DVO DVH and Dose calculation DVH are showed equal value in IMRT treatment plan. But AAA calculation shows lack of dose compared with DVO result which is satisfactory condition. Optimizing VMAT treatment plans using PRO II obtained results were satisfactory, but lower density area showed lack of dose in dose calculations. PRO III, but optimizing the dose calculation results were similar with optimized the same conditions once more. In this study, do not judge the rightness of the dose

  6. Mobile Launch Platform Vehicle Assembly Area (SWMU 056) Biosparge Expansion Interim Measures Work Plan

    Science.gov (United States)

    Burcham, Michael S.; Daprato, Rebecca C.

    2016-01-01

    This document presents the design details for an Interim Measure (IM) Work Plan (IMWP) for the Mobile Launch Platform/Vehicle Assembly Building (MLPV) Area, located at the John F. Kennedy Space Center (KSC), Florida. The MLPV Area has been designated Solid Waste Management Unit Number 056 (SWMU 056) under KSC's Resource Conservation and Recovery Act (RCRA) Corrective Action Program. This report was prepared by Geosyntec Consultants (Geosyntec) for the National Aeronautics and Space Administration (NASA) under contract number NNK09CA02B and NNK12CA13B, project control number ENV1642. The Advanced Data Package (ADP) presentation covering the elements of this IMWP report received KSC Remediation Team (KSCRT) approval at the December 2015 Team Meeting; the meeting minutes are included in Appendix A.

  7. The DOE Office of Environmental Management International Cooperative Program: Current Status and Plans for Expansion

    International Nuclear Information System (INIS)

    Gerdes, Kurt D.; Han, Ana M.; Marra, James C.; Fox, Kevin M.; Peeler, David K.; Smith, Michael E.; Jannik, Gerald T.; Farfan, Eduardo B.; Kim, Dong-Sang; Vienna, John D.; Roach, Jay; Aloy, A.S.; Stefanovsky, S.V.; Bondarkov, M.D.; Lopukh, D.P.; Kim, Chenwoo

    2009-01-01

    The DOE-EM Office of Engineering and Technology is responsible for implementing EM's international cooperative program. The Office of Engineering and Technology's international efforts are aimed at supporting EM's mission of risk reduction and accelerated cleanup of the environmental legacy of the nation's nuclear weapons program and government-sponsored nuclear energy research. To do this, EM pursues collaborations with government organizations, educational institutions, and private industry to identify and develop technologies that can address the site cleanup needs of DOE. Currently, DOE-EM is performing collaborative work with researchers at the Khlopin Radium Institute (KRI) and the SIA Radon Institute in Russia and the Ukraine's International Radioecology Laboratory (IRL). Additionally, a task was recently completed with the Nuclear Engineering Technology Institute (NETEC) in South Korea. The objectives of these collaborations were to explore issues relating to high-level waste and to investigate technologies that could be leveraged to support EM site cleanup needs. In FY09, continued collaboration with the current partners is planned. Additionally, new research projects are being planned to expand the International Program. A collaborative project with Russian Electrotechnical University is underway to evaluate CCIM control and monitoring technologies. A Statement of Intent was recently signed between DOE-EM and the U.K. Nuclear Decommissioning Authority (NDA) to work cooperatively on areas of mutual interest. Under this umbrella, discussions were held with NDA representatives to identify potential areas for collaboration. Information and technical exchanges were identified as near-term actions to help meet the objectives of the Statement of Intent. Technical exchanges in identified areas are being pursued in FY09.

  8. Continuous 4-1BB co-stimulatory signals for the optimal expansion of tumor-infiltrating lymphocytes for adoptive T-cell therapy.

    Science.gov (United States)

    Chacon, Jessica Ann; Pilon-Thomas, Shari; Sarnaik, Amod A; Radvanyi, Laszlo G

    2013-09-01

    Co-stimulation through members of the tumor necrosis factor receptor (TNFR) family appears to be critical for the generation of T cells with optimal effector-memory properties for adoptive cell therapy. Our work suggests that continuous 4-1BB/CD137 co-stimulation is required for the expansion of T cells with an optimal therapeutic profile and that the administration of 4-1BB agonists upon adoptive cell transfer further improves antitumor T-cell functions.

  9. Regulatory Impacts on Distributed Generation and Upstream Transmission Substation Expansion Planning: A Novel Stochastic Bi-level Model

    Directory of Open Access Journals (Sweden)

    F. Misaghi

    2017-06-01

    Full Text Available In this paper, a novel framework is proposed to study impacts of regulatory incentive on distributed generation (DG investment in sub-transmission substations, as well as upgrading of upstream transmission substations. Both conventional and wind power technologies are considered here. Investment incentives are fuel cost, firm contracts, capacity payment and investment subsidy relating to wind power. The problem is modelled as a bi-level stochastic optimization problem, where the upper level consists of investor's decisions maximizing its own profit. Both market clearing and decision on upgrading of transmission substation aiming at minimizing the total cost are considered in the lower level. Due to non-convexity of the lower level and impossibility of converting to single level problem (i.e. mathematical programming with equilibrium constraints (MPEC, an algorithm combing enumeration and mathematical optimization is used to tackle with the non-convexity. For each upgrading strategy of substations, a stochastic MPEC, converted to a mixed integer linear programming (MILP is solved. The proposed model is examined on a six-bus and an actual network. Numerical studies confirm that the proposed model can be used for analysing investment behaviour of DGs and substation expansion.

  10. An Optimization Model and Modified Harmony Search Algorithm for Microgrid Planning with ESS

    Directory of Open Access Journals (Sweden)

    Yang Jiao

    2017-01-01

    Full Text Available To solve problems such as the high cost of microgrids (MGs, balance between supply and demand, stability of system operation, and optimizing the MG planning model, the energy storage system (ESS and harmony search algorithm (HSA are proposed. First, the conventional MG planning optimization model is constructed and the constraint conditions are defined: the supply and demand balance and reserve requirements. Second, an ESS is integrated into the optimal model of MG planning. The model with an ESS can solve and identify parameters such as the optimal power, optimal capacity, and optimal installation year. Third, the convergence speed and robustness of the ESS are optimized and improved. A case study comprising three different cases concludes the paper. The results show that the modified HSA (MHSA can effectively improve the stability and economy of MG operation with an ESS.

  11. Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

    Science.gov (United States)

    Salehi, Mojtaba; Bahreininejad, Ardeshir

    2011-08-01

    Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

  12. The US DOE Office of Environmental Management International Cooperative Program: Current Status and Plans for Expansion

    International Nuclear Information System (INIS)

    Gerdes, K.D.; Han, A.M.; Marra, J.C.; Fox, K.M.; Peeler, D.K.; Smith, M.E.; Jannik, G.T.; Farfan, E.B.; Kim, D.S.; Vienna, J.D.; Roach, J.A.; Aloy, A.S.; Stefanovsky, S.V.; Bondarkov, M.D.; Lopukh, D.P.; Kim, C.W.

    2009-01-01

    monitoring, analytical measurements, and numerical modeling of soils and groundwater radioactive contamination; and - Recommend the development and testing of effective cleanup technologies to reduce environmental and health risks. In FY09, continued collaboration with the current partners is planned. Additionally, new research projects are being planned to expand the international program. A collaborative project with Russian Electrotechnical University is underway to evaluate Cold Crucible Induction Melter (CCIM) control and monitoring technologies. A Statement of Intent was recently signed between DOE-EM and the U.K. Nuclear Decommissioning Authority (NDA) to work cooperatively on areas of mutual interest. Under this umbrella, discussions were held with NDA representatives to identify potential areas for collaboration. Information and technical exchanges were identified as near-term actions to help meet the objectives of the Statement of Intent. Technical exchanges in identified areas are being pursued in FY09. (authors)

  13. Procedures for Dealing with Optimism Bias in Transport Planning

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Glenting, Carsten; Rønnest, Arne Kvist

    of the document are to provide empirically based optimism bias up-lifts for selected reference classes of transport infrastructure projects and provide guidance on using the established uplifts to produce more realistic forecasts for the individual project's capital expenditures. Furthermore, the underlying...... causes and institutional context for optimism bias in British transport projects are discussed and some possibilities for reducing optimism bias in project preparation and decision-making are identified....

  14. Generating Optimal Stowage Plans for Container Vessel Bays

    DEFF Research Database (Denmark)

    Delgado-Ortegon, Alberto; Jensen, Rune Møller; Schulte, Christian

    2009-01-01

    collaboration to date with a liner shipping company on automated stowage planning. We then show how to solve this model ef- ficiently in - to our knowledge - the first application of CP to stowage planning using state-of-the-art techniques such as extensive use of global constraints, viewpoints, static...

  15. Simultaneous optimization of planning and scheduling in an oil refinery

    NARCIS (Netherlands)

    Zondervan, E.; van Boekel, T.P.J.; Fransoo, J.C.; Haan, de A.B.; Postikopoulos, E.N.; Georgiadis, M.C.; Kokossis, A.

    2011-01-01

    In earlier work we have developed and tested a scheduling model [1] in the AIMMS software. In this follow-up contribution we will develop a planning model. Next we will identify the information flow between scheduling model and the planning model. Lastly we will integrate the two models in a

  16. Integrated production planning and control: A multi-objective optimization model

    Directory of Open Access Journals (Sweden)

    Cheng Wang

    2013-09-01

    Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise

  17. Optimal, Generic Planning of Maintenance and Inspection of Steel Bridges

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, Michael Havbro

    2002-01-01

    Fatigue damage is an important deterioration mechanism for steel bridges. This paper describes a simplified and generic approach for reliability and risk based inspection planning of fatigue sensitive structural details. Fatigue sensitive details are categorized according to their loading charact...

  18. Machine Learning for Earth Observation Flight Planning Optimization

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper is a progress report of an effort whose goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth...

  19. MO-D-BRC-04: Multiple-Criteria Optimization Planning

    Energy Technology Data Exchange (ETDEWEB)

    Donaghue, J. [Akron General Medical Center (United States)

    2016-06-15

    Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical.

  20. MO-D-BRC-04: Multiple-Criteria Optimization Planning

    International Nuclear Information System (INIS)

    Donaghue, J.

    2016-01-01

    Treatment planning is a central part of radiation therapy, including delineation in tumor volumes and critical organs, setting treatment goals of prescription doses to the tumor targets and tolerance doses to the critical organs, and finally generation of treatment plans to meet the treatment goals. National groups like RTOG have led the effort to standardize treatment goals of the prescription doses to the tumor targets and tolerance doses to the critical organs based on accumulated knowledge from decades of abundant clinical trial experience. The challenge for each clinical department is how to achieve or surpass these set goals within the time constraints of clinical practice. Using fifteen testing cases from different treatment sites such as head and neck, prostate with and without pelvic lymph nodes, SBRT spine, we will present clinically utility of advanced planning tools, including knowledge based, automatic based, and multiple criteria based tools that are clinically implemented. The objectives of this session are: Understand differences among these three advanced planning tools Provide clinical assessments on the utility of the advanced planning tools Discuss clinical challenges of treatment planning with large variations in tumor volumes and their relationships with adjacent critical organs. Ping Xia received research grant from Philips. Jackie Wu received research grant from Varian; P. Xia, Research support by Philips and Varian; Q. Wu, NIH, Varian Medical

  1. Implementation of the robustness analysis methodology for decenal planning in the expansion of electric sector; Aplicacao da metodologia de analise de robustez ao planejamento decenal de expansao do setor eletrico

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Renata de Azevedo Moreira da

    2008-05-15

    The objective of this dissertation is to develop an application from one of the techniques of 'soft' operational research, the Robustness Analysis, to the problem of decision making under uncertainty, as part of the planning of the electricity expansion planning process in Brazil. Initially are shown desirable characteristics of a methodology that will complement the traditional methods used in determining the expansion of the sector. Departing from the Decenal Plan for Power Expansion (2007/2016), an analysis of the different trends that can occur during the planning process is presented, so as to facilitate the visualization of the consequences of uncertainties that may change the schedule of the planned expansion and also help the interaction between actors working in the expansion planning of electricity generation. (author)

  2. Implementation of the robustness analysis methodology for decenal planning in the expansion of electric sector; Aplicacao da metodologia de analise de robustez ao planejamento decenal de expansao do setor eletrico

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Renata de Azevedo Moreira da

    2008-05-15

    The objective of this dissertation is to develop an application from one of the techniques of 'soft' operational research, the Robustness Analysis, to the problem of decision making under uncertainty, as part of the planning of the electricity expansion planning process in Brazil. Initially are shown desirable characteristics of a methodology that will complement the traditional methods used in determining the expansion of the sector. Departing from the Decenal Plan for Power Expansion (2007/2016), an analysis of the different trends that can occur during the planning process is presented, so as to facilitate the visualization of the consequences of uncertainties that may change the schedule of the planned expansion and also help the interaction between actors working in the expansion planning of electricity generation. (author)

  3. Evaluation of plan quality assurance models for prostate cancer patients based on fully automatically generated Pareto-optimal treatment plans.

    Science.gov (United States)

    Wang, Yibing; Breedveld, Sebastiaan; Heijmen, Ben; Petit, Steven F

    2016-06-07

    IMRT planning with commercial Treatment Planning Systems (TPSs) is a trial-and-error process. Consequently, the quality of treatment plans may not be consistent among patients, planners and institutions. Recently, different plan quality assurance (QA) models have been proposed, that could flag and guide improvement of suboptimal treatment plans. However, the performance of these models was validated using plans that were created using the conventional trail-and-error treatment planning process. Consequently, it is challenging to assess and compare quantitatively the accuracy of different treatment planning QA models. Therefore, we created a golden standard dataset of consistently planned Pareto-optimal IMRT plans for 115 prostate patients. Next, the dataset was used to assess the performance of a treatment planning QA model that uses the overlap volume histogram (OVH). 115 prostate IMRT plans were fully automatically planned using our in-house developed TPS Erasmus-iCycle. An existing OVH model was trained on the plans of 58 of the patients. Next it was applied to predict DVHs of the rectum, bladder and anus of the remaining 57 patients. The predictions were compared with the achieved values of the golden standard plans for the rectum D mean, V 65, and V 75, and D mean of the anus and the bladder. For the rectum, the prediction errors (predicted-achieved) were only  -0.2  ±  0.9 Gy (mean  ±  1 SD) for D mean,-1.0  ±  1.6% for V 65, and  -0.4  ±  1.1% for V 75. For D mean of the anus and the bladder, the prediction error was 0.1  ±  1.6 Gy and 4.8  ±  4.1 Gy, respectively. Increasing the training cohort to 114 patients only led to minor improvements. A dataset of consistently planned Pareto-optimal prostate IMRT plans was generated. This dataset can be used to train new, and validate and compare existing treatment planning QA models, and has been made publicly available. The OVH model was highly accurate

  4. A stochastic multi-agent optimization model for energy infrastructure planning under uncertainty and competition.

    Science.gov (United States)

    2017-07-04

    This paper presents a stochastic multi-agent optimization model that supports energy infrastruc- : ture planning under uncertainty. The interdependence between dierent decision entities in the : system is captured in an energy supply chain network, w...

  5. PROBLEMS OF ROUTE NETWORK AND AIRCRAFT FLEET OPTIMIZATION AS A SPECIFIC TASK OF AIRLINE STRATEGIC PLANNING

    Directory of Open Access Journals (Sweden)

    M. A. Karakuts

    2015-01-01

    Full Text Available The basic problems of route network and aircraft fleet optimization and its role in airline strategic planning are considered. Measures to improve the methods of its implementation are proposed.

  6. Optimization of Gamma Knife treatment planning via guided evolutionary simulated annealing

    International Nuclear Information System (INIS)

    Zhang Pengpeng; Dean, David; Metzger, Andrew; Sibata, Claudio

    2001-01-01

    We present a method for generating optimized Gamma Knife trade mark sign (Elekta, Stockholm, Sweden) radiosurgery treatment plans. This semiautomatic method produces a highly conformal shot packing plan for the irradiation of an intracranial tumor. We simulate optimal treatment planning criteria with a probability function that is linked to every voxel in a volumetric (MR or CT) region of interest. This sigmoidal P + parameter models the requirement of conformality (i.e., tumor ablation and normal tissue sparing). After determination of initial radiosurgery treatment parameters, a guided evolutionary simulated annealing (GESA) algorithm is used to find the optimal size, position, and weight for each shot. The three-dimensional GESA algorithm searches the shot parameter space more thoroughly than is possible during manual shot packing and provides one plan that is suitable to the treatment criteria of the attending neurosurgeon and radiation oncologist. The result is a more conformal plan, which also reduces redundancy, and saves treatment administration time

  7. Applied Railway Optimization in Production Planning at DSB-S-tog - Tasks, Tools and Challenges

    DEFF Research Database (Denmark)

    Clausen, Jens

    2007-01-01

    these conflicting goals. S-tog has therefore on the strategic level decided to use software with optimization capabilities in the planning processes. We describe the current status for each activity using optimization or simulation as a tool: Timetable evaluation, rolling stock planning, and crew scheduling...... to the customers, and has concurrently been met with demands for higher efficiency in the daily operation. The plans of timetable, rolling stock and crew must hence allow for a high level of customer service, be efficient, and be robust against disturbances of operations. It is a highly non-trivial task to meet....... In addition we describe on-going efforts in using mathematical models in activities such as timetable design and work-force planning. We also identify some organizatorial key factors, which have paved the way for extended use of optimization methods in railway production planning....

  8. MULTI-CRITERIA PROGRAMMING METHODS AND PRODUCTION PLAN OPTIMIZATION PROBLEM SOLVING IN METAL INDUSTRY

    OpenAIRE

    Tunjo Perić; Željko Mandić

    2017-01-01

    This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method) in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained resul...

  9. SU-D-BRD-01: Cloud-Based Radiation Treatment Planning: Performance Evaluation of Dose Calculation and Plan Optimization

    International Nuclear Information System (INIS)

    Na, Y; Kapp, D; Kim, Y; Xing, L; Suh, T

    2014-01-01

    Purpose: To report the first experience on the development of a cloud-based treatment planning system and investigate the performance improvement of dose calculation and treatment plan optimization of the cloud computing platform. Methods: A cloud computing-based radiation treatment planning system (cc-TPS) was developed for clinical treatment planning. Three de-identified clinical head and neck, lung, and prostate cases were used to evaluate the cloud computing platform. The de-identified clinical data were encrypted with 256-bit Advanced Encryption Standard (AES) algorithm. VMAT and IMRT plans were generated for the three de-identified clinical cases to determine the quality of the treatment plans and computational efficiency. All plans generated from the cc-TPS were compared to those obtained with the PC-based TPS (pc-TPS). The performance evaluation of the cc-TPS was quantified as the speedup factors for Monte Carlo (MC) dose calculations and large-scale plan optimizations, as well as the performance ratios (PRs) of the amount of performance improvement compared to the pc-TPS. Results: Speedup factors were improved up to 14.0-fold dependent on the clinical cases and plan types. The computation times for VMAT and IMRT plans with the cc-TPS were reduced by 91.1% and 89.4%, respectively, on average of the clinical cases compared to those with pc-TPS. The PRs were mostly better for VMAT plans (1.0 ≤ PRs ≤ 10.6 for the head and neck case, 1.2 ≤ PRs ≤ 13.3 for lung case, and 1.0 ≤ PRs ≤ 10.3 for prostate cancer cases) than for IMRT plans. The isodose curves of plans on both cc-TPS and pc-TPS were identical for each of the clinical cases. Conclusion: A cloud-based treatment planning has been setup and our results demonstrate the computation efficiency of treatment planning with the cc-TPS can be dramatically improved while maintaining the same plan quality to that obtained with the pc-TPS. This work was supported in part by the National Cancer Institute (1

  10. SU-D-BRD-01: Cloud-Based Radiation Treatment Planning: Performance Evaluation of Dose Calculation and Plan Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Na, Y; Kapp, D; Kim, Y; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Suh, T [Catholic UniversityMedical College, Seoul, Seoul (Korea, Republic of)

    2014-06-01

    Purpose: To report the first experience on the development of a cloud-based treatment planning system and investigate the performance improvement of dose calculation and treatment plan optimization of the cloud computing platform. Methods: A cloud computing-based radiation treatment planning system (cc-TPS) was developed for clinical treatment planning. Three de-identified clinical head and neck, lung, and prostate cases were used to evaluate the cloud computing platform. The de-identified clinical data were encrypted with 256-bit Advanced Encryption Standard (AES) algorithm. VMAT and IMRT plans were generated for the three de-identified clinical cases to determine the quality of the treatment plans and computational efficiency. All plans generated from the cc-TPS were compared to those obtained with the PC-based TPS (pc-TPS). The performance evaluation of the cc-TPS was quantified as the speedup factors for Monte Carlo (MC) dose calculations and large-scale plan optimizations, as well as the performance ratios (PRs) of the amount of performance improvement compared to the pc-TPS. Results: Speedup factors were improved up to 14.0-fold dependent on the clinical cases and plan types. The computation times for VMAT and IMRT plans with the cc-TPS were reduced by 91.1% and 89.4%, respectively, on average of the clinical cases compared to those with pc-TPS. The PRs were mostly better for VMAT plans (1.0 ≤ PRs ≤ 10.6 for the head and neck case, 1.2 ≤ PRs ≤ 13.3 for lung case, and 1.0 ≤ PRs ≤ 10.3 for prostate cancer cases) than for IMRT plans. The isodose curves of plans on both cc-TPS and pc-TPS were identical for each of the clinical cases. Conclusion: A cloud-based treatment planning has been setup and our results demonstrate the computation efficiency of treatment planning with the cc-TPS can be dramatically improved while maintaining the same plan quality to that obtained with the pc-TPS. This work was supported in part by the National Cancer Institute (1

  11. Optimal savings management for individuals with defined contribution pension plans

    DEFF Research Database (Denmark)

    Konicz, Agnieszka Karolina; Mulvey, John M.

    2015-01-01

    (or time left to retirement), nor should they solely depend on the risk preferences, but should also capture: (1) economical characteristics—such as current value on the pension savings account, expected pension contributions (mandatory and voluntary), and expected income after retirement (e...... characterizing the individual. The problem is solved via a model that combines two optimization approaches: stochastic optimal control and multi-stage stochastic programming. The first method is common in financial and actuarial literature, but produces theoretical results. However, the latter, which...

  12. The generation expansion planning of the Brazilian electric sector employing genetic algorithms; O planejamento da expansao da geracao do setor eletrico brasileiro utilizando os algoritmos geneticos

    Energy Technology Data Exchange (ETDEWEB)

    Kazay, Heloisa Firmo

    2001-07-01

    The generation expansion-planning problem is a non-linear large-scale optimisation problem, which is even larger when it refers to the Brazilian system, and when one considers the multiple intervening uncertainty sources. To handle the complexity of the problem, decomposition schemes have been used. Usually, such schemes divide the expansion problem into two sub-problems: one related to the construction of new plants (investment sub-problem) and another dealing with the task of operating the system (operation sub-problem). This thesis proposes a genetic algorithm to solve the investment sub-problem. Initially, an analysis of the state of the art on the generation expansion planning and the field of the genetic algorithms are presented. Then follows a practical application of the proposed algorithm in a model of generation expansion planning under uncertainty. Finally, the results obtained in two case studies are presented and analysed. These results indicate that the proposed genetic algorithm is an effective alternative to the solution of the investment sub-problem. (author)

  13. UBB expansion plan: Spain

    OpenAIRE

    Sousa, André Henderson

    2014-01-01

    Project of Master in International Management Just like the Portuguese saying “who runs for fun does not get tired”. UBB, a textile merchandising brand for Universities has been founded by four friends in 2012. It all started when Rui and André noticed that in their university there was no official merchandising. They saw a window of opportunity of bringing something new to the fore, which was an alternative for universities to have an official merchandising line without any monetar...

  14. Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms

    Science.gov (United States)

    Babier, Aaron; Boutilier, Justin J.; Sharpe, Michael B.; McNiven, Andrea L.; Chan, Timothy C. Y.

    2018-05-01

    We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate ‘inverse plans’ that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to

  15. Automated Planning of Tangential Breast Intensity-Modulated Radiotherapy Using Heuristic Optimization

    International Nuclear Information System (INIS)

    Purdie, Thomas G.; Dinniwell, Robert E.; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B.

    2011-01-01

    Purpose: To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. Method and Materials: A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle 3 ) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. Results: The mean time to generate a complete treatment plan was 6 min, 50 s ± 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. Conclusion: We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical practice.

  16. INDUSTRIAL ENTERPRISE TAX PLANNING AS PART OF EXPENSE OPTIMIZATION STRATEGY

    Directory of Open Access Journals (Sweden)

    A. P. Garnov

    2012-01-01

    Full Text Available Tax liability planning is vital for industrial enterprises to reduce their tax burden and thus reduce expenses of the organization for a certain period. Industrial enterprises are among main taxpayers in the Russian Federation, and recommendations given in the article on topical issues related to planning of tax obligations will help top managers of the enterprises to avoid unnecessary financial losses and to ensure further growth and development of their organizations. Attention is focused on specifics of the industrial enterprises’ activities under present conditions due to the nature and particular features of their operation.

  17. INDUSTRIAL ENTERPRISE TAX PLANNING AS PART OF EXPENSE OPTIMIZATION STRATEGY

    Directory of Open Access Journals (Sweden)

    A. P. Garnov

    2012-01-01

    Full Text Available Tax liability planning is vital for industrial enterprises to reduce their tax burden and thus reduce expenses of the organization for a certain period. Industrial enterprises are among main taxpayers in the Russian Federation, and recommendations given in the article on topical issues relatedto planning of tax obligations will help top managers of the enterprises to avoid unnecessary financial losses and to ensure further growth and development of their organizations. Attention is focused on specifics of the industrial enterprises’ activities under present conditions due to thenature and particular features of their operation.

  18. ''Training plan optimized design'' methodology application to IBERDROLA - Power generation

    International Nuclear Information System (INIS)

    Gil, S.; Mendizabal, J.L.

    1996-01-01

    The trend in both Europe and the United States, towards the understanding that no training plan may be considered suitable if not backed by the results of application of the S.A.T. (Systematic Approach to Training) methodology, led TECNATOM, S.A. to apply thy methodology through development of an application specific to the conditions of the Spanish working system. The requirement that design of the training be coherent with the realities of the working environment is met by systematic application of the SAT methodology as part of the work analysis and job-based task analysis processes, this serving as a basis for design of the training plans

  19. Optimization of the Actuarial Model of Defined Contribution Pension Plan

    Directory of Open Access Journals (Sweden)

    Yan Li

    2014-01-01

    Full Text Available The paper focuses on the actuarial models of defined contribution pension plan. Through assumptions and calculations, the expected replacement ratios of three different defined contribution pension plans are compared. Specially, more significant considerable factors are put forward in the further cost and risk analyses. In order to get an assessment of current status, the paper finds a relationship between the replacement ratio and the pension investment rate using econometrics method. Based on an appropriate investment rate of 6%, an expected replacement ratio of 20% is reached.

  20. Sequential use of simulation and optimization in analysis and planning

    Science.gov (United States)

    Hans R. Zuuring; Jimmie D. Chew; J. Greg Jones

    2000-01-01

    Management activities are analyzed at landscape scales employing both simulation and optimization. SIMPPLLE, a stochastic simulation modeling system, is initially applied to assess the risks associated with a specific natural process occurring on the current landscape without management treatments, but with fire suppression. These simulation results are input into...

  1. Optimal Inspection Planning for Fatigue Damage of Offshore Structures

    DEFF Research Database (Denmark)

    Madsen, H.O.; Sørensen, John Dalsgaard; Olesen, R.

    1990-01-01

    A formulation of optimal design, inspection and maintenance against damage caused by fatigue crack growth is formulated. A stochastic model for fatigue crack growth based on linear elastic fracture mechanics Is applied. Failure is defined by crack growth beyond a critical crack size. The failure ...

  2. Brachytherapy optimal planning with application to intravascular radiation therapy

    DEFF Research Database (Denmark)

    Sadegh, Payman; Mourtada, Firas A.; Taylor, Russell H.

    1999-01-01

    determination of an optimal dwell-time sequence for a train of seeds that deliver ratiation while stepping through the vessel lesion. The results illustrate the advantage of this strategy over the common approach of delivering radiation by positioning a single train of seeds along the whole lesion....

  3. Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

    Science.gov (United States)

    Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

    2016-02-01

    A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

  4. Wildlife Conservation Planning Using Stochastic Optimization and Importance Sampling

    Science.gov (United States)

    Robert G. Haight; Laurel E. Travis

    1997-01-01

    Formulations for determining conservation plans for sensitive wildlife species must account for economic costs of habitat protection and uncertainties about how wildlife populations will respond. This paper describes such a formulation and addresses the computational challenge of solving it. The problem is to determine the cost-efficient level of habitat protection...

  5. Planning and Optimization Methods for Active Distribution Systems

    DEFF Research Database (Denmark)

    Abbey, Chad; Baitch, Alex; Bak-Jensen, Birgitte

    distribution planning. Active distribution networks (ADNs) have systems in place to control a combination of distributed energy resources (DERs), defined as generators, loads and storage. With these systems in place, the AND becomes an Active Distribution System (ADS). Distribution system operators (DSOs) have...

  6. Optimization-based decision support systems for planning problems in processing industries

    NARCIS (Netherlands)

    Claassen, G.D.H.

    2014-01-01

    Summary

    Optimization-based decision support systems for planning problems in processing industries

    Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in

  7. Reliability-Based Optimal Design of Experiment Plans for Offshore Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, Michael Havbro; Kroon, I. B.

    1993-01-01

    Design of cost optimal experiment plans on the basis of a preposterior analysis is discussed. In particular the planning of on-site response measurements on offshore structures in order to update probabilistic models for fatigue life estimation is addressed. Special emphasis is given to modelling...

  8. Critical path method as the criterion for optimization of business planning process

    OpenAIRE

    Butsenko Elena V.

    2016-01-01

    In today's economy the task of improving business planning is considered a necessary component of any enterprise management process and is precisely the solution drawn from that task which determines the financial policy and economic structure. The development of technologies based on the optimization of business planning is a very urgent scientific challenge. In this paper we propose to use the methods of network planning and management as a tool for economic and mathematical modeling to...

  9. Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response

    OpenAIRE

    Agosta, John Mark

    2013-01-01

    This paper works through the optimization of a real world planning problem, with a combination of a generative planning tool and an influence diagram solver. The problem is taken from an existing application in the domain of oil spill emergency response. The planning agent manages constraints that order sets of feasible equipment employment actions. This is mapped at an intermediate level of abstraction onto an influence diagram. In addition, the planner can apply a surveillance operator that...

  10. Commercial Aircraft Trajectory Planning based on Multiphase Mixed-Integer Optimal Control

    OpenAIRE

    Soler Arnedo, Manuel Fernando

    2017-01-01

    The main goal of this dissertation is to develop optimal control techniques for aircraft trajectory planning looking at reduction of fuel consumption, emissions and overfly charges in flight plans. The calculation of a flight plan involves the consideration of multiple factors. They can be classified as either continuous or discrete, and include nonlinear aircraft performance, atmospheric conditions, wind conditions, airspace structure, amount of departure fuel, and operational...

  11. Compiling Planning into Quantum Optimization Problems: A Comparative Study

    Science.gov (United States)

    2015-06-07

    to SAT, and then reduces higher order terms to quadratic terms through a series of gadgets . Our mappings allow both positive and negative preconditions...to its being specific to this type of problem) and likely benefits from an homogeneous parameter setting (Venturelli et al. 2014), as it generates a...Guzik, A. 2013. Resource efficient gadgets for compiling adiabatic quan- tum optimization problems. Annalen der Physik 525(10- 11):877–888. Blum, A

  12. Optimized path planning for soft tissue resection via laser vaporization

    Science.gov (United States)

    Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick

    2018-02-01

    Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.

  13. Advantages and limitations of navigation-based multicriteria optimization (MCO) for localized prostate cancer IMRT planning

    International Nuclear Information System (INIS)

    McGarry, Conor K.; Bokrantz, Rasmus; O’Sullivan, Joe M.; Hounsell, Alan R.

    2014-01-01

    Efficacy of inverse planning is becoming increasingly important for advanced radiotherapy techniques. This study’s aims were to validate multicriteria optimization (MCO) in RayStation (v2.4, RaySearch Laboratories, Sweden) against standard intensity-modulated radiation therapy (IMRT) optimization in Oncentra (v4.1, Nucletron BV, the Netherlands) and characterize dose differences due to conversion of navigated MCO plans into deliverable multileaf collimator apertures. Step-and-shoot IMRT plans were created for 10 patients with localized prostate cancer using both standard optimization and MCO. Acceptable standard IMRT plans with minimal average rectal dose were chosen for comparison with deliverable MCO plans. The trade-off was, for the MCO plans, managed through a user interface that permits continuous navigation between fluence-based plans. Navigated MCO plans were made deliverable at incremental steps along a trajectory between maximal target homogeneity and maximal rectal sparing. Dosimetric differences between navigated and deliverable MCO plans were also quantified. MCO plans, chosen as acceptable under navigated and deliverable conditions resulted in similar rectal sparing compared with standard optimization (33.7 ± 1.8 Gy vs 35.5 ± 4.2 Gy, p = 0.117). The dose differences between navigated and deliverable MCO plans increased as higher priority was placed on rectal avoidance. If the best possible deliverable MCO was chosen, a significant reduction in rectal dose was observed in comparison with standard optimization (30.6 ± 1.4 Gy vs 35.5 ± 4.2 Gy, p = 0.047). Improvements were, however, to some extent, at the expense of less conformal dose distributions, which resulted in significantly higher doses to the bladder for 2 of the 3 tolerance levels. In conclusion, similar IMRT plans can be created for patients with prostate cancer using MCO compared with standard optimization. Limitations exist within MCO regarding conversion of navigated plans to

  14. Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

    International Nuclear Information System (INIS)

    Tahvili, Sahar; Österberg, Jonas; Silvestrov, Sergei; Biteus, Jonas

    2014-01-01

    One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation

  15. Study on hybrid multi-objective optimization algorithm for inverse treatment planning of radiation therapy

    International Nuclear Information System (INIS)

    Li Guoli; Song Gang; Wu Yican

    2007-01-01

    Inverse treatment planning for radiation therapy is a multi-objective optimization process. The hybrid multi-objective optimization algorithm is studied by combining the simulated annealing(SA) and genetic algorithm(GA). Test functions are used to analyze the efficiency of algorithms. The hybrid multi-objective optimization SA algorithm, which displacement is based on the evolutionary strategy of GA: crossover and mutation, is implemented in inverse planning of external beam radiation therapy by using two kinds of objective functions, namely the average dose distribution based and the hybrid dose-volume constraints based objective functions. The test calculations demonstrate that excellent converge speed can be achieved. (authors)

  16. Optimal Orientation Planning and Control Deviation Estimation on FAST Cable-Driven Parallel Robot

    Directory of Open Access Journals (Sweden)

    Hui Li

    2014-03-01

    Full Text Available The paper is devoted theoretically to the optimal orientation planning and control deviation estimation of FAST cable-driven parallel robot. Regarding the robot characteristics, the solutions are obtained from two constrained optimizations, both of which are based on the equilibrium of the cabin and the attention on force allocation among 6 cable tensions. A kind of control algorithm is proposed based on the position and force feedbacks. The analysis proves that the orientation control depends on force feedback and the optimal tension solution corresponding to the planned orientation. Finally, the estimation of orientation deviation is given under the limit range of tension errors.

  17. Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

    Energy Technology Data Exchange (ETDEWEB)

    Tahvili, Sahar [Mälardalen University (Sweden); Österberg, Jonas; Silvestrov, Sergei [Division of Applied Mathematics, Mälardalen University (Sweden); Biteus, Jonas [Scania CV (Sweden)

    2014-12-10

    One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

  18. Artificial immune system for diabetes meal plans optimization

    Science.gov (United States)

    Prilianti, K. R.; Callista, P. B.; Setiawan, H.

    2017-03-01

    Type 2 diabetes mellitus is a disease that occurs because the body lacks of insulin or the insulin produced by the pancreas cannot work effectively such that the glucose level in the blood cannot well controlled. One of the most common causes of diabetes mellitus type 2 is obesity, therefore this disease can be controlled with the appropriate diet regarding to the daily calorie requirement. Hence, the level of blood glucose is maintained. Unfortunately, because the lack of proper diet education and facility, many people cannot work on proper daily healthy diet by their own. In this research Artificial Immune System algorithm was applied to build a model that help diabetes mellitus patient arrange their meal plans. The model can calculate the amount of daily calorie needed and arrange the appropriate daily meal plans based on it. The meal plans vary according to the patient calorie needs. The required input data are age, gender, weight, height, and type of patient daily main activity. The experiments show that this model has a good result. The result is already approaching the patients' daily calorie need, i.e. 97.6% (actual need is not less than 80% and not greater than 100%). Carbohydrate of the meal plan is 55-57% (actual need is not less than 45% and not greater than 60%) whereas the protein approximate 15-18% (actual need is not less than 15% and not greater than 20%) and fat of approximate 22-24% (actual need is not less than 20% and not greater than 25%).

  19. Globally Optimal Path Planning with Anisotropic Running Costs

    Science.gov (United States)

    2013-03-01

    Eikonal equation and has numerous applications, for exam- ple, in path planning, computational geometry, computer vision, and image enhancement...Sethian 1999b]. Numerical methods for solving the Eikonal equation include Tsitsiklis’ control-theoretic algorithm [Tsitsiklis 1995], Fast Marching Methods...methods for Eikonal equations on triangular meshes, SIAM J. Numer. Anal. 45(1), 83—107. Rowe, M. P., Sidhu, H. S. & Mercer, G. N. (2009) Military

  20. Integrated production-distribution planning optimization models: A review in collaborative networks context

    Directory of Open Access Journals (Sweden)

    Beatriz Andres

    2017-01-01

    Full Text Available Researchers in the area of collaborative networks are more and more aware of proposing collaborative approaches to address planning processes, due to the advantages associated when enterprises perform integrated planning models. Collaborative production-distribution planning, among the supply network actors, is considered a proper mechanism to support enterprises on dealing with uncertainties and dynamicity associated to the current markets. Enterprises, and especially SMEs, should be able to overcome the continuous changes of the market by increasing their agility. Carrying out collaborative planning allows enterprises to enhance their readiness and agility for facing the market turbulences. However, SMEs have limited access when incorporating optimization tools to deal with collaborative planning, reducing their ability to respond to the competition. The problem to solve is to provide SMEs affordable solutions to support collaborative planning. In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. As part of the H2020 Cloud Collaborative Manufacturing Networks (C2NET research project, this paper presents a study on integrated production and distribution plans. The main objective of the research is to identify gaps in current optimization models, proposed to address integrated planning, taking into account the requirements and needs of the industry. Thus, the needs of the companies belonging to the industrial pilots, defined in the C2NET project, are identified; analysing how these needs are covered by the optimization models proposed in the literature, to deal with the integrated production-distribution planning.

  1. Radiation dose optimization in the decommissioning plan for Loviisa NPP

    Energy Technology Data Exchange (ETDEWEB)

    Holmberg, R.; Eurajoki, T. [Nuclear Power Engineering (Finland)

    1995-03-01

    Finnish rules for nuclear power require a detailed decommissioning plan to be made and kept up to date already during plant operation. The main reasons for this {open_quotes}premature{close_quotes} plan, is, firstly, the need to demonstrate the feasibility of decommissioning, and, secondly, to make realistic cost estimates in order to fund money for this future operation. The decomissioning for Lovissa Nuclear Power Plant (NPP) (2{times}445 MW, PWR) was issued in 1987. It must be updated about every five years. One important aspect of the plant is an estimate of radiation doses to the decomissioning workers. The doses were recently re-estimated because of a need to decrease the total collective dose estimate in the original plan, 23 manSv. In the update, the dose was reduced by one-third. Part of the reduction was due to changes in the protection and procedures, in which ALARA considerations were taken into account, and partly because of re-estimation of the doses.

  2. Optimization in radiotherapy treatment planning thanks to a fast dose calculation method

    International Nuclear Information System (INIS)

    Yang, Mingchao

    2014-01-01

    This thesis deals with the radiotherapy treatments planning issue which need a fast and reliable treatment planning system (TPS). The TPS is composed of a dose calculation algorithm and an optimization method. The objective is to design a plan to deliver the dose to the tumor while preserving the surrounding healthy and sensitive tissues. The treatment planning aims to determine the best suited radiation parameters for each patient's treatment. In this thesis, the parameters of treatment with IMRT (Intensity modulated radiation therapy) are the beam angle and the beam intensity. The objective function is multi-criteria with linear constraints. The main objective of this thesis is to demonstrate the feasibility of a treatment planning optimization method based on a fast dose-calculation technique developed by (Blanpain, 2009). This technique proposes to compute the dose by segmenting the patient's phantom into homogeneous meshes. The dose computation is divided into two steps. The first step impacts the meshes: projections and weights are set according to physical and geometrical criteria. The second step impacts the voxels: the dose is computed by evaluating the functions previously associated to their mesh. A reformulation of this technique makes possible to solve the optimization problem by the gradient descent algorithm. The main advantage of this method is that the beam angle parameters could be optimized continuously in 3 dimensions. The obtained results in this thesis offer many opportunities in the field of radiotherapy treatment planning optimization. (author) [fr

  3. Optimal design and planning of glycerol-based biorefinery supply chains under uncertainty

    DEFF Research Database (Denmark)

    Loureiro da Costa Lira Gargalo, Carina; Carvalho, Ana; Gernaey, Krist V.

    2017-01-01

    -echelon mixed integer linear programming problem is proposed based upon a previous model, GlyThink. In the new formulation, market uncertainties are taken into account at the strategic planning level. The robustness of the supply chain structures is analyzed based on statistical data provided...... by the implementation of the Monte Carlo method, where a deterministic optimization problem is solved for each scenario. Furthermore, the solution of the stochastic multi-objective optimization model, points to the Pareto set of trade-off solutions obtained when maximizing the NPV and minimizing environmental......The optimal design and planning of glycerol-based biorefinery supply chains is critical for the development and implementation of this concept in a sustainable manner. To achieve this, a decision-making framework is proposed in this work, to holistically optimize the design and planning...

  4. Multi-objective Transmission Planning Paper

    DEFF Research Database (Denmark)

    Xu, Zhao; Dong, Zhao Yang; Wong, Kit Po

    2009-01-01

    This paper describes a transmission expansion planning method based on multi-objective optimization (MOOP). The method starts with constructing a candidate pool of feasible expansion plans, followed by selection of the best candidates through MOOP, of which multiple objectives are tackled...

  5. Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

    Science.gov (United States)

    Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

    2015-12-01

    For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

  6. The equivalence of multi-criteria methods for radiotherapy plan optimization

    International Nuclear Information System (INIS)

    Breedveld, Sebastiaan; Storchi, Pascal R M; Heijmen, Ben J M

    2009-01-01

    Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2pεc (2-phase ε-constraint) method is based on the ε-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.

  7. Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

    International Nuclear Information System (INIS)

    Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Foote, Matthew; Lehman, Margot; Chan, Lawrence Wing Chi

    2017-01-01

    Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

  8. Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Foote, Matthew; Lehman, Margot [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)

    2017-07-01

    Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

  9. Determination of Optimal Double Sampling Plan using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Sampath Sundaram

    2012-03-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Designing double sampling plan requires identification of sample sizes and acceptance numbers. In this paper a genetic algorithm has been designed for the selection of optimal acceptance numbers and sample sizes for the specified producer’s risk and consumer’s risk. Implementation of the algorithm has been illustrated numerically for different choices of quantities involved in a double sampling plan   

  1. MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

    Energy Technology Data Exchange (ETDEWEB)

    Feng, W. [New York Presbyterian Hospital (United States)

    2015-06-15

    The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequential events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d) semi

  2. Planning a sports training program using Adaptive Particle Swarm Optimization with emphasis on physiological constraints.

    Science.gov (United States)

    Kumyaito, Nattapon; Yupapin, Preecha; Tamee, Kreangsak

    2018-01-08

    An effective training plan is an important factor in sports training to enhance athletic performance. A poorly considered training plan may result in injury to the athlete, and overtraining. Good training plans normally require expert input, which may have a cost too great for many athletes, particularly amateur athletes. The objectives of this research were to create a practical cycling training plan that substantially improves athletic performance while satisfying essential physiological constraints. Adaptive Particle Swarm Optimization using ɛ-constraint methods were used to formulate such a plan and simulate the likely performance outcomes. The physiological constraints considered in this study were monotony, chronic training load ramp rate and daily training impulse. A comparison of results from our simulations against a training plan from British Cycling, which we used as our standard, showed that our training plan outperformed the benchmark in terms of both athletic performance and satisfying all physiological constraints.

  3. Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

    Science.gov (United States)

    Poder, Joel; Whitaker, May

    2016-06-01

    Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected.

  4. A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

    Science.gov (United States)

    Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

    2015-04-07

    Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation

  5. A Study on the optimal distribution planning using computer system

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Soon Tae; Mun, Byung Hwa; Jang, Jung Tae; Hwang, Su Cheun; Kim, Ju Yong [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center; Mun, Young Hwan; Choi, Sang Bong [Korea Inst. of Energy and Resources, Daeduk (Korea, Republic of); Kim, Jae Cheul; Han, Sung Ho [Electrical Engineering and Science Research Institute (Korea, Republic of)

    1996-12-31

    The main purpose of this study is to improve the CADPAD package to be convenient for the user and solve problems possibly to be emerged in application to three real distribution system of KEPCO (Kandong, Chungnam, Changwon branch) and retrofit the DISCAN program such as its modification of output function mouse manipulation, load creation / allocation, on-line help. In addition, problems concerned with practical application of investment / financing planning, load forecasting technique and reliability of system have been reviewed and also methods to raise the function of the package for extended application to other KEPCO`s distribution systems including interface with the programs already in use have been studied. (author). 61 refs., 114 figs.

  6. A Study on the optimal distribution planning using computer system

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Soon Tae; Mun, Byung Hwa; Jang, Jung Tae; Hwang, Su Cheun; Kim, Ju Yong [Korea Electric Power Corp. (KEPCO), Taejon (Korea, Republic of). Research Center; Mun, Young Hwan; Choi, Sang Bong [Korea Inst. of Energy and Resources, Daeduk (Korea, Republic of); Kim, Jae Cheul; Han, Sung Ho [Electrical Engineering and Science Research Institute (Korea, Republic of)

    1995-12-31

    The main purpose of this study is to improve the CADPAD package to be convenient for the user and solve problems possibly to be emerged in application to three real distribution system of KEPCO (Kandong, Chungnam, Changwon branch) and retrofit the DISCAN program such as its modification of output function mouse manipulation, load creation / allocation, on-line help. In addition, problems concerned with practical application of investment / financing planning, load forecasting technique and reliability of system have been reviewed and also methods to raise the function of the package for extended application to other KEPCO`s distribution systems including interface with the programs already in use have been studied. (author). 61 refs., 114 figs.

  7. 'Optimized' 3-D planning by simple means. An example

    International Nuclear Information System (INIS)

    Richter, S.; Flentje, M.; Richter, J.

    2000-01-01

    Aim: A treatment technique favorable for linacs with asymmetric jaws, which combines cranio-caudal matching fields with fields enclosing the whole target volume, is investigated with respect to field matching and sparing of normal tissue and organs at risk. Patient and methods: For a pelvic target volume rapidly varying in cranio-caudal direction a 5-field technique was planned with individually weighted and blocked fields. Three fields adjoining in cranio-caudal direction were completed by 2 fields enclosing the whole target volume. The matching line was measured and calculated with helax TMS copyright . Furthermore, a 4-field box and opposing fields were planned. The dose-volume histograms for target, bladder, intestine and soft tissue were exported. Normal tissue complication probability and tumor control probability, respectively, were calculated for all techniques. Results: In the region of the matching line the summation of the measured normalized curves resulted in relative dose maxima of 6.0% (caudal) and 4.5% (cranial), respectively. For fields enclosing the whole target volume the dose maxima in the region of the matching line decreased to 2.0% (caudal) and 1.8% (cranial), respectively. For the dose profiles calculated with Helax TMS copyright no overdose was found. The 5-field technique with adjoining fields results in a better sparing of the organs at risk compared to the other techniques, wheres the tumor control remains the same. Conclusions: In specific cases a technique with cranio-caudal adjoining fields can be recommended with respect to sparing of normal tissue and organs at risk. (orig.) [de

  8. System of optimization computations of five year plans in the coal industry. [USSR

    Energy Technology Data Exchange (ETDEWEB)

    Goyzman, E I; Korenev, V G

    1980-01-01

    A system of optimization computations of five year plans is set forth which was developed over a number of years at the Central Scientific Research Institute of Economics and Scientific-Technical Information of the Coal Industry. Basic principles of design and methodological approaches are given which were used in development of the systemas well as levels of administration and information links between them. The report analyzes the characteristics of problems of planning which arise at different stages of formation of the five year plans and discusses possibilities of taking into account these characteristics in optimized models. Economic formulations of problems of optimization of five year plans are given as applied to two levels of administration: at the branch level and at the level of production associations. Economic-mathematical models of optimization of five year plans are developed for each of the levels and their characteristic features described. The primary methodological principles, on the basis of which optimization models were developed are examined. An economic-mathematical model with continuous variables was developed for the branch level of planning. Volumes of recovery according to a group of shafts in the stage of normal operation (stable group) of each production enterprise are adopted as model variables. A system of limitations which includes limitations on volumes and distinguishable resources is formulated. The minimum of operating expenses, minimum of capital investments and maximum of recovery volumes for the planned period can be used as the optimization criteria. An economic-mathematical model which uses integral variable was developed for the production association level.

  9. Multiobjective optimization with a modified simulated annealing algorithm for external beam radiotherapy treatment planning

    International Nuclear Information System (INIS)

    Aubry, Jean-Francois; Beaulieu, Frederic; Sevigny, Caroline; Beaulieu, Luc; Tremblay, Daniel

    2006-01-01

    Inverse planning in external beam radiotherapy often requires a scalar objective function that incorporates importance factors to mimic the planner's preferences between conflicting objectives. Defining those importance factors is not straightforward, and frequently leads to an iterative process in which the importance factors become variables of the optimization problem. In order to avoid this drawback of inverse planning, optimization using algorithms more suited to multiobjective optimization, such as evolutionary algorithms, has been suggested. However, much inverse planning software, including one based on simulated annealing developed at our institution, does not include multiobjective-oriented algorithms. This work investigates the performance of a modified simulated annealing algorithm used to drive aperture-based intensity-modulated radiotherapy inverse planning software in a multiobjective optimization framework. For a few test cases involving gastric cancer patients, the use of this new algorithm leads to an increase in optimization speed of a little more than a factor of 2 over a conventional simulated annealing algorithm, while giving a close approximation of the solutions produced by a standard simulated annealing. A simple graphical user interface designed to facilitate the decision-making process that follows an optimization is also presented

  10. Pre-optimization of radiotherapy treatment planning: an artificial neural network classification aided technique

    International Nuclear Information System (INIS)

    Hosseini-Ashrafi, M.E.; Bagherebadian, H.; Yahaqi, E.

    1999-01-01

    A method has been developed which, by using the geometric information from treatment sample cases, selects from a given data set an initial treatment plan as a step for treatment plan optimization. The method uses an artificial neural network (ANN) classification technique to select a best matching plan from the 'optimized' ANN database. Separate back-propagation ANN classifiers were trained using 50, 60 and 77 examples for three groups of treatment case classes (up to 21 examples from each class were used). The performance of the classifiers in selecting the correct treatment class was tested using the leave-one-out method; the networks were optimized with respect their architecture. For the three groups used in this study, successful classification fractions of 0.83, 0.98 and 0.93 were achieved by the optimized ANN classifiers. The automated response of the ANN may be used to arrive at a pre-plan where many treatment parameters may be identified and therefore a significant reduction in the steps required to arrive at the optimum plan may be achieved. Treatment planning 'experience' and also results from lengthy calculations may be used for training the ANN. (author)

  11. Planning oral narrative tasks: optimizing strategic planning condition through strategy instruction

    Directory of Open Access Journals (Sweden)

    André Luís Specht

    2017-06-01

    Full Text Available This article presents the results of a master thesis, which aimed at investigating the impact of strategic planning instruction on the speech performance of 6 L2 Brazilian learners. The participants, Letras-Inglês students, performed three now-and-there picture-cued narrative tasks under three different conditions: (1 no planning, (2 planning before instruction, and (3 planning after instruction. In addition, the participants filled in post-task questionnaires after the performance of each task, aiming at understanding their opinion on the conditions and tasks. Quantitative and qualitative analyses were conducted in order to examine participants’ oral production and perception, respectively. In general, there was no statistical evidence supporting the impact of instruction on participants’ oral planned performance; however, some statistical results approached significance, which may suggest some positive effects. Qualitative analyses provided positive evidence of the impact of strategic planning instruction on participant perception and their use of strategies during planning time. Moreover, the results of this study can contribute to the fields of Second Language Acquisition and Language Pegadogy.

  12. Multiobjective planning of distribution networks incorporating switches and protective devices using a memetic optimization

    International Nuclear Information System (INIS)

    Pombo, A. Vieira; Murta-Pina, João; Pires, V. Fernão

    2015-01-01

    A multi-objective planning approach for the reliability of electric distribution networks using a memetic optimization is presented. In this reliability optimization, the type of the equipment (switches or reclosers) and their location are optimized. The multiple objectives considered to find the optimal values for these planning variables are the minimization of the total equipment cost and at the same time the minimization of two distribution network reliability indexes. The reliability indexes are the system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI). To solve this problem a memetic evolutionary algorithm is proposed, which combines the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with a local search algorithm. The obtained Pareto-optimal front contains solutions of different trade-offs with respect to the three objectives. A real distribution network is used to test the proposed algorithm. The obtained results show that this approach allows the utility to obtain the optimal type and location of the equipments to achieve the best reliability with the lower cost. - Highlights: • Reliability indexes SAIFI and SAIDI and Equipment Cost are optimized. • Optimization of equipment type, number and location on a MV network. • Memetic evolutionary algorithm with a local search algorithm is proposed. • Pareto optimal front solutions with respect to the three objective functions

  13. Threshold-driven optimization for reference-based auto-planning

    Science.gov (United States)

    Long, Troy; Chen, Mingli; Jiang, Steve; Lu, Weiguo

    2018-02-01

    We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used voxel-based quadratic penalties have two components for penalizing under- and over-dosing of voxels: a reference dose threshold and associated penalty weight. Conventional manual- and auto-planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and often inconsistent method for planning toward some reference DVH. However, driving a dose distribution by threshold values instead of preference weights can achieve similar plans with less computational effort. The proposed methodology spatially assigns reference DVH information to threshold values, and iteratively improves the quality of that assignment. The methodology effectively handles both sub-optimal and infeasible DVHs. TORA was applied to a prostate case and a liver case as a proof-of-concept. Reference DVHs were generated using a conventional voxel-based objective, then altered to be either infeasible or easy-to-achieve. TORA was able to closely recreate reference DVHs in 5-15 iterations of solving a simple convex sub-problem. TORA has the potential to be effective for auto-planning based on reference DVHs. As dose prediction and knowledge-based planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, efficient way will be crucial for automated planning. A threshold-focused objective tuning should be explored over conventional methods of updating preference weights for DVH-guided treatment planning.

  14. Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

    Directory of Open Access Journals (Sweden)

    B. Mashadi

    Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.

  15. TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

    2014-06-15

    Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.

  16. Therapeutic treatment plan optimization with probability density-based dose prescription

    International Nuclear Information System (INIS)

    Lian Jun; Cotrutz, Cristian; Xing Lei

    2003-01-01

    The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process

  17. Joint optimization of preventive maintenance and spare parts inventory for an optimal production plan with consideration of CO_2 emission

    International Nuclear Information System (INIS)

    Ba, Kader; Dellagi, Sofiene; Rezg, Nidhal; Erray, Walid

    2016-01-01

    This article presents a joint optimization of spare parts inventory and preventive maintenance. While minimizing CO_2 emissions, this approach is based on an optimal production plan achieved thanks to the HMMS model. The process which is studied in this paper only manufactures one type of product. The purpose of the paper is to determine for a random demand over a given period, a cost-effective production plan and a maintenance policy which integrates a spare parts strategy in accordance with environmental requirements and regulations. Our green spare parts management can be defined as a set of actions that are applied in order to decrease the spare parts footprint in its lifetime (Ba et al., 2015) [1]. Indeed, we take into account the spare parts characteristics (new or used) which will be used during maintenance actions (preventive or corrective) to preserve the environment. Consequently, we set up analytical models based on the effect of the production rate on the system deterioration so as to substantially cut the maintenance costs, production costs and CO_2 emissions. To evaluate the performance of our models, we give some illustrative examples. - Highlights: • Establishment of an optimal production plan for a manufacturing process. • Cost-effective maintenance strategy with a green spare parts strategy. • Possibility to choose between used and new spare parts to execute maintenance action.

  18. A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization

    International Nuclear Information System (INIS)

    Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.

    2014-01-01

    Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly

  19. Comparison of optimization algorithms in intensity-modulated radiation therapy planning

    Science.gov (United States)

    Kendrick, Rachel

    Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.

  20. Optimization of RFID network planning using Zigbee and WSN

    Science.gov (United States)

    Hasnan, Khalid; Ahmed, Aftab; Badrul-aisham, Bakhsh, Qadir

    2015-05-01

    Everyone wants to be ease in their life. Radio frequency identification (RFID) wireless technology is used to make our life easier. RFID technology increases productivity, accuracy and convenience in delivery of service in supply chain. It is used for various applications such as preventing theft of automobiles, tolls collection without stopping, no checkout lines at grocery stores, managing traffic, hospital management, corporate campuses and airports, mobile asset tracking, warehousing, tracking library books, and to track a wealth of assets in supply chain management. Efficiency of RFID can be enhanced by integrating with wireless sensor network (WSN), zigbee mesh network and internet of things (IOT). The proposed system is used for identifying, sensing and real-time locating system (RTLS) of items in an indoor heterogeneous region. The system gives real-time richer information of object's characteristics, location and their environmental parameters like temperature, noise and humidity etc. RTLS reduce human error, optimize inventory management, increase productivity and information accuracy at indoor heterogeneous network. The power consumption and the data transmission rate of the system can be minimized by using low power hardware design.

  1. Problems of future energy market planning and optimization

    International Nuclear Information System (INIS)

    Vladimir Lelek; David Jaluvka

    2007-01-01

    Problems of future energy supply in the form, which is demanded - heat, liquid fuel, electricity - are described. There are several factors, which probably could be studied separately: technology and its sustain ability with respect to the raw materials resources, long time for capacity construction, for some form of energy even absence of sufficiently deep technology knowledge and model of prices. Prices are specially peculiar problem - they could be very different from the standard approach (investment, operation and maintenance, fuel, profit), if there are market instabilities and you are not able to supply market by the demanded amount form of energy with the consequences on production. Expected effect will be jump in prices or regulated supply to equalize supply and use. Such situation will be until the new capacities are put into operation or new technologies of production are established - it could be time about ten or more years and this can completely change our standard consideration of profit. The main profit will be to avoid losses and unemployment. Also concept of local or domestic raw material resources could be changed - in the free market your resources will be sold to those paying more. Probable development of energy market is described in the article and special attention is devoted to the nuclear energy, which not only consume, but also produce raw material and how to proceed to avoid crises in supply. Contemporary understanding of the problem does not enable to formulate it strictly as mathematical optimization task (Authors)

  2. Energy Resource Planning. Optimal utilization of energy resources

    International Nuclear Information System (INIS)

    Miclescu, T.; Domschke, W.; Bazacliu, G.; Dumbrava, V.

    1996-01-01

    For a thermal power plants system, the primary energy resources cost constitutes a significant percentage of the total system operational cost. Therefore a small percentage saving in primary energy resource allocation cost for a long term, often turns out to be a significant monetary value. In recent years, with a rapidly changing fuel supply situation, including the impact of energy policies changing, this area has become extremely sensitive. Natural gas availability has been restricted in many areas, coal production and transportation cost have risen while productivity has decreased, oil imports have increased and refinery capacity failed to meet demand. The paper presents a mathematical model and a practical procedure to solve the primary energy resource allocation. The objectives is to minimise the total energy cost over the planning period subject to constraints with regards to primary energy resource, transportation and energy consumption. Various aspects of the proposed approach are discussed, and its application to a power system is illustrated.(author) 2 figs., 1 tab., 3 refs

  3. SVC Planning in Large–scale Power Systems via a Hybrid Optimization Method

    DEFF Research Database (Denmark)

    Yang, Guang ya; Majumder, Rajat; Xu, Zhao

    2009-01-01

    The research on allocation of FACTS devices has attracted quite a lot interests from various aspects. In this paper, a hybrid model is proposed to optimise the number, location as well as the parameter settings of static Var compensator (SVC) deployed in large–scale power systems. The model...... utilises the result of vulnerability assessment for determining the candidate locations. A hybrid optimisation method including two stages is proposed to find out the optimal solution of SVC in large– scale planning problem. In the first stage, a conventional genetic algorithm (GA) is exploited to generate...... a candidate solution pool. Then in the second stage, the candidates are presented to a linear planning model to investigate the system optimal loadability, hence the optimal solution for SVC planning can be achieved. The method is presented to IEEE 300–bus system....

  4. Optimal Planning and Operation Management of a Ship Electrical Power System with Energy Storage System

    DEFF Research Database (Denmark)

    Anvari-Moghaddam, Amjad; Dragicevic, Tomislav; Meng, Lexuan

    2016-01-01

    Next generation power management at all scales is highly relying on the efficient scheduling and operation of different energy sources to maximize efficiency and utility. The ability to schedule and modulate the energy storage options within energy systems can also lead to more efficient use...... of the generating units. This optimal planning and operation management strategy becomes increasingly important for off-grid systems that operate independently of the main utility, such as microgrids or power systems on marine vessels. This work extends the principles of optimal planning and economic dispatch...... for the proposed plan is derived based on the solution from a mixed-integer nonlinear programming (MINLP) problem. Simulation results showed that including well-sized energy storage options together with optimal operation management of generating units can improve the economic operation of the test system while...

  5. A complex systems approach to planning, optimization and decision making for energy networks

    International Nuclear Information System (INIS)

    Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

    2008-01-01

    This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock

  6. Maximizing dosimetric benefits of IMRT in the treatment of localized prostate cancer through multicriteria optimization planning

    International Nuclear Information System (INIS)

    Wala, Jeremiah; Craft, David; Paly, Jon; Zietman, Anthony; Efstathiou, Jason

    2013-01-01

    We examine the quality of plans created using multicriteria optimization (MCO) treatment planning in intensity-modulated radiation therapy (IMRT) in treatment of localized prostate cancer. Nine random cases of patients receiving IMRT to the prostate were selected. Each case was associated with a clinically approved plan created using Corvus. The cases were replanned using MCO-based planning in RayStation. Dose-volume histogram data from both planning systems were presented to 2 radiation oncologists in a blinded evaluation, and were compared at a number of dose-volume points. Both physicians rated all 9 MCO plans as superior to the clinically approved plans (p −5 ). Target coverage was equivalent (p = 0.81). Maximum doses to the prostate and bladder and the V50 and V70 to the anterior rectum were reduced in all MCO plans (p<0.05). Treatment planning time with MCO took approximately 60 minutes per case. MCO-based planning for prostate IMRT is efficient and produces high-quality plans with good target homogeneity and sparing of the anterior rectum, bladder, and femoral heads, without sacrificing target coverage

  7. Maximizing dosimetric benefits of IMRT in the treatment of localized prostate cancer through multicriteria optimization planning

    Energy Technology Data Exchange (ETDEWEB)

    Wala, Jeremiah; Craft, David [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Paly, Jon [Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Zietman, Anthony [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States); Efstathiou, Jason, E-mail: jefstathiou@partners.org [Harvard Medical School, Boston, MA (United States); Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA (United States)

    2013-10-01

    We examine the quality of plans created using multicriteria optimization (MCO) treatment planning in intensity-modulated radiation therapy (IMRT) in treatment of localized prostate cancer. Nine random cases of patients receiving IMRT to the prostate were selected. Each case was associated with a clinically approved plan created using Corvus. The cases were replanned using MCO-based planning in RayStation. Dose-volume histogram data from both planning systems were presented to 2 radiation oncologists in a blinded evaluation, and were compared at a number of dose-volume points. Both physicians rated all 9 MCO plans as superior to the clinically approved plans (p<10{sup −5}). Target coverage was equivalent (p = 0.81). Maximum doses to the prostate and bladder and the V50 and V70 to the anterior rectum were reduced in all MCO plans (p<0.05). Treatment planning time with MCO took approximately 60 minutes per case. MCO-based planning for prostate IMRT is efficient and produces high-quality plans with good target homogeneity and sparing of the anterior rectum, bladder, and femoral heads, without sacrificing target coverage.

  8. Clinical treatment planning optimization by Powell's method for gamma unit treatment system

    International Nuclear Information System (INIS)

    Yan Yulong; Shu Huazhong; Bao Xudong; Luo Limin; Bai Yi

    1997-01-01

    Purpose: This article presents a new optimization method for stereotactic radiosurgery treatment planning for gamma unit treatment system. Methods and Materials: The gamma unit has been utilized in stereotactic radiosurgery for about 30 years, but the usual procedure for a physician-physicist team to design a treatment plan is a trial-and-error approach. Isodose curves are viewed on two-dimensional computed tomography (CT) or magnetic resonance (MR) image planes, which is not only time consuming but also seldom achieves the optimal treatment plan, especially when the isocenter weights are regarded. We developed a treatment-planning system on a computer workstation in which Powell's optimization method is realized. The optimization process starts with the initial parameters (the number of iso centers as well as corresponding 3D iso centers' coordinates, collimator sizes, and weight factors) roughly determined by the physician-physicist team. The objective function can be changed to consider protection of sensitive tissues. Results: We use the plan parameters given by a well-trained physician-physicist team, or ones that the author give roughly as the initial parameters for the optimization procedure. Dosimetric results of optimization show a better high dose-volume conformation to the target volume compared to the doctor's plan. Conclusion: This method converges quickly and is not sensitive to the initial parameters. It achieves an excellent conformation of the estimated isodose curves with the contours of the target volume. If the initial parameters are varied, there will be a little difference in parameters' configuration, but the dosimetric results proved almost to be the same

  9. Application of particle swarm optimization algorithm in the heating system planning problem.

    Science.gov (United States)

    Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

    2013-01-01

    Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem.

  10. Multi-GPU configuration of 4D intensity modulated radiation therapy inverse planning using global optimization

    Science.gov (United States)

    Hagan, Aaron; Sawant, Amit; Folkerts, Michael; Modiri, Arezoo

    2018-01-01

    We report on the design, implementation and characterization of a multi-graphic processing unit (GPU) computational platform for higher-order optimization in radiotherapy treatment planning. In collaboration with a commercial vendor (Varian Medical Systems, Palo Alto, CA), a research prototype GPU-enabled Eclipse (V13.6) workstation was configured. The hardware consisted of dual 8-core Xeon processors, 256 GB RAM and four NVIDIA Tesla K80 general purpose GPUs. We demonstrate the utility of this platform for large radiotherapy optimization problems through the development and characterization of a parallelized particle swarm optimization (PSO) four dimensional (4D) intensity modulated radiation therapy (IMRT) technique. The PSO engine was coupled to the Eclipse treatment planning system via a vendor-provided scripting interface. Specific challenges addressed in this implementation were (i) data management and (ii) non-uniform memory access (NUMA). For the former, we alternated between parameters over which the computation process was parallelized. For the latter, we reduced the amount of data required to be transferred over the NUMA bridge. The datasets examined in this study were approximately 300 GB in size, including 4D computed tomography images, anatomical structure contours and dose deposition matrices. For evaluation, we created a 4D-IMRT treatment plan for one lung cancer patient and analyzed computation speed while varying several parameters (number of respiratory phases, GPUs, PSO particles, and data matrix sizes). The optimized 4D-IMRT plan enhanced sparing of organs at risk by an average reduction of 26% in maximum dose, compared to the clinical optimized IMRT plan, where the internal target volume was used. We validated our computation time analyses in two additional cases. The computation speed in our implementation did not monotonically increase with the number of GPUs. The optimal number of GPUs (five, in our study) is directly related to the

  11. Comparison of various online IGRT strategies: The benefits of online treatment plan re-optimization

    International Nuclear Information System (INIS)

    Schulze, Derek; Liang, Jian; Yan, Di; Zhang Tiezhi

    2009-01-01

    Purpose: To compare the dosimetric differences of various online IGRT strategies and to predict potential benefits of online re-optimization techniques in prostate cancer radiation treatments. Materials and methods: Nine prostate patients were recruited in this study. Each patient has one treatment planning CT images and 10-treatment day CT images. Five different online IGRT strategies were evaluated which include 3D conformal with bone alignment, 3D conformal re-planning via aperture changes, intensity modulated radiation treatment (IMRT) with bone alignment, IMRT with target alignment and IMRT daily re-optimization. Treatment planning and virtual treatment delivery were performed. The delivered doses were obtained using in-house deformable dose mapping software. The results were analyzed using equivalent uniform dose (EUD). Results: With the same margin, rectum and bladder doses in IMRT plans were about 10% and 5% less than those in CRT plans, respectively. Rectum and bladder doses were reduced as much as 20% if motion margin is reduced by 1 cm. IMRT is more sensitive to organ motion. Large discrepancies of bladder and rectum doses were observed compared to the actual delivered dose with treatment plan predication. The therapeutic ratio can be improved by 14% and 25% for rectum and bladder, respectively, if IMRT online re-planning is employed compared to the IMRT bone alignment approach. The improvement of target alignment approach is similar with 11% and 21% dose reduction to rectum and bladder, respectively. However, underdosing in seminal vesicles was observed on certain patients. Conclusions: Online treatment plan re-optimization may significantly improve therapeutic ratio in prostate cancer treatments mostly due to the reduction of PTV margin. However, for low risk patient with only prostate involved, online target alignment IMRT treatment would achieve similar results as online re-planning. For all IGRT approaches, the delivered organ-at-risk doses may be

  12. A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

    Science.gov (United States)

    Basdekas, L.; Stewart, N.; Triana, E.

    2013-12-01

    Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU

  13. A critical evaluation of worst case optimization methods for robust intensity-modulated proton therapy planning

    International Nuclear Information System (INIS)

    Fredriksson, Albin; Bokrantz, Rasmus

    2014-01-01

    Purpose: To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. Methods: The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. Results: If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. Conclusions: The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas

  14. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    Energy Technology Data Exchange (ETDEWEB)

    AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

    2011-10-15

    Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  15. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    International Nuclear Information System (INIS)

    AlRashidi, M.R.; AlHajri, M.F.

    2011-01-01

    Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  16. Simulation-optimization model for production planning in the blood supply chain.

    Science.gov (United States)

    Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A

    2017-12-01

    Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

  17. MULTI-CRITERIA PROGRAMMING METHODS AND PRODUCTION PLAN OPTIMIZATION PROBLEM SOLVING IN METAL INDUSTRY

    Directory of Open Access Journals (Sweden)

    Tunjo Perić

    2017-09-01

    Full Text Available This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained results indicate a high efficiency of the applied methods in solving the problem.

  18. A robust optimization model for agile and build-to-order supply chain planning under uncertainties

    DEFF Research Database (Denmark)

    Lalmazloumian, Morteza; Wong, Kuan Yew; Govindan, Kannan

    2016-01-01

    Supply chain planning as one of the most important processes within the supply chain management concept, has a great impact on firms' success or failure. This paper considers a supply chain planning problem of an agile manufacturing company operating in a build-to-order environment under various....... The formulation is a robust optimization model with the objective of minimizing the expected total supply chain cost while maintaining customer service level. The developed multi-product, multi-period, multi-echelon robust mixed-integer linear programming model is then solved using the CPLEX optimization studio...

  19. Optimizing production and imperfect preventive maintenance planning's integration in failure-prone manufacturing systems

    International Nuclear Information System (INIS)

    Aghezzaf, El-Houssaine; Khatab, Abdelhakim; Tam, Phuoc Le

    2016-01-01

    This paper investigates the issue of integrating production and maintenance planning in a failure-prone manufacturing system. It is assumed that the system's operating state is stochastically predictable, in terms of its operating age, and that it can accordingly be preventively maintained during preplanned periods. Preventive maintenance is assumed to be imperfect, that is when performed, it brings the manufacturing system to an operating state that lies between ‘as bad as old’ and ‘as good as new’. Only an overhauling of the system brings it to a ‘as good as new’ operating state again. A practical integrated production and preventive maintenance planning model, that takes into account the system's manufacturing capacity and its operational reliability state, is developed. The model is naturally formulated as a mixed-integer non-linear optimization problem, for which an extended mixed-integer linear reformulation is proposed. This reformulation, while it solves the proposed integrated planning problem to optimality, remains quite demanding in terms of computational time. A fix-and-optimize procedure, that takes advantage of some properties of the original model, is then proposed. The reformulation and the fix-and-optimize procedure are tested on some test instances adapted from those available in the literature. The results show that the proposed fix-and-optimize procedure performs quite well and opens new research direction for future improvements. - Highlights: • Integration of production planning and imperfect preventive maintenance is explored. • Imperfect maintenance is modeled using a fitting age reduction hybrid hazard rate. • A practical approximate optimization model for this integration is proposed. • The resulting naturally MINL optimization model is reformulated and solved as a MILP. • An effective fix-and-optimize procedure is proposed for large instances of this MILP.

  20. A new column-generation-based algorithm for VMAT treatment plan optimization

    International Nuclear Information System (INIS)

    Peng Fei; Epelman, Marina A; Romeijn, H Edwin; Jia Xun; Gu Xuejun; Jiang, Steve B

    2012-01-01

    We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose–volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25–55 s. (paper)

  1. Optimal radiation port arrangements for hepatic tumor using 3-dimensional conformal radiotherapy planning

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ik Jae; Seong, Jin Sil; Shim, Su Jung; Jeong, Kyoung Keun [Yonsei Univ., Seoul (Korea, Republic of); Cho, Kwang Hwan [Sunchunhyang Univ., Buchon (Korea, Republic of)

    2006-12-15

    The purpose of this study was to investigate the optimal beam arrangements for hepatic tumors, according to the location of the hepatic tumor and its relationship to Organs At Risk (OARs). The virtual gross tumor volumes were divided into four groups according to the Couinaud's classification. Several plans were made for each virtual target, and these plans were compared for the Normal Tissue Complication Probabilities (NTCP). For group I, NTCP improved as the number of the beam ports increased. However, plans with more than 5 ports had little advantage. For group II, plans with the beam directions from the anterior side showed better results. Group III contained many OARs near the target, which placed restrictions on the beam-directions. Multi-directional plans yielded a higher dose to the OARs than a simple two-port plan using right anterior oblique and posterior beam (RAO/PA). For group IV, a simple RAO/PA port plan was adequate for protection of remaining liver. NTCP can significantly vary between radiotherapy plans when the location of the tumor and its neighboring OARs are taken into consideration. The results in this study of optimal beam arrangements could be a useful set of guidelines for radiotherapy of hepatic tumors.

  2. SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B [University Medical Center Utrecht, Utrecht (Netherlands); Breedveld, S; Sharfo, A; Heijmen, B [Erasmus University Medical Center Rotterdam, Rotterdam (Netherlands)

    2016-06-15

    Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan

  3. SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

    International Nuclear Information System (INIS)

    Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B; Breedveld, S; Sharfo, A; Heijmen, B

    2016-01-01

    Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan

  4. Optimization-based decision support systems for planning problems in processing industries

    OpenAIRE

    Claassen, G.D.H.

    2014-01-01

    Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

  5. Optimal planning of gas turbine cogeneration system based on linear programming. Paper no. IGEC-1-ID09

    International Nuclear Information System (INIS)

    Oh, S.-D.; Kwak, H.-Y.

    2005-01-01

    An optimal planning for gas turbine cogeneration system has been studied. The planning problem considered in this study is to determine the optimal configuration of the system equipments and optimal operational policy of the system when the annual energy demands of electric power, heat and cooling are given a priori. The main benefit of the optimal planning is to minimize operational costs and to save energy by efficient energy utilization. A mixed-integer linear programming and the branch and bound algorithm have been adopted to obtain the optimal solution. Both the optimal configuration of the system equipments and the optimal operation policy has been obtained based on annual cost method. The planning method employed here may be applied to the planning problem of the cogeneration plant to any specific building or hotel. (author)

  6. An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios

    International Nuclear Information System (INIS)

    Tolis, Athanasios I.; Rentizelas, Athanasios A.

    2011-01-01

    Highlights: → The impact of electricity and CO 2 allowance pricing in power sector is researched. → A stochastic programming approach without recourse is used for the optimisation. → Higher electricity prices may be proportionally beneficial for the power system. → The CO 2 allowance prices may be inversely proportionate with the expected yields. → High CO 2 allowance prices are inhibitors for conventional technology projects. -- Abstract: The present work concerns a systematic investigation of power sector portfolios through discrete scenarios of electricity and CO 2 allowance prices. The analysis is performed for different prices, from regulated to completely deregulated markets, thus representing different electricity market policies. The modelling approach is based on a stochastic programming algorithm without recourse, used for the optimisation of power sector economics under multiple uncertainties. A sequential quadratic programming routine is applied for the entire investigation period whilst the time-dependent objective function is subject to various social and production constraints, usually confronted in power sectors. The analysis indicated the optimal capacity additions that should be annually ordered from each competitive technology in order to substantially improve both the economy and the sustainability of the system. It is confirmed that higher electricity prices lead to higher financial yields of power production, irrespective of the CO 2 allowance price level. Moreover, by following the proposed licensing planning, a medium-term reduction of CO 2 emissions per MW h by 30% might be possible. Interestingly, the combination of electricity prices subsidisation with high CO 2 allowance prices may provide favourable conditions for investors willing to engage on renewable energy markets.

  7. TH-CD-209-06: LET-Based Adjustment of IMPT Plans Using Prioritized Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Unkelbach, J; Giantsoudi, D; Paganetti, H [Massachusetts General Hospital, Boston, MA (United States); Botas, P [Massachusetts General Hospital, Boston, MA (United States); Heidelberg University, Heidelberg, DE (Germany); Qin, N; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

    2016-06-15

    Purpose: In-vitro experiments suggest an increase in proton relative biological effectiveness (RBE) towards the end of range. However, proton treatment planning and dose reporting for clinical outcome assessment has been based on physical dose and constant RBE. Therefore, treatment planning for intensity-modulated proton therapy (IMPT) is unlikely to transition radically to pure RBE-based planning. We suggest a hybrid approach where treatment plans are initially created based on physical dose constraints and prescriptions, and are subsequently altered to avoid high linear energy transfer (LET) in critical structures while limiting the degradation of the physical dose distribution. Methods: To allow fast optimization based on dose and LET we extended a GPU-based Monte-Carlo code towards providing dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of physical dose and LET (LETxD). To first approximation, LETxD represents a measure of the additional biological dose that is caused by high LET. Regarding optimization techniques, LETxD has the advantage of being a linear function of the pencil beam intensities. Results: The method is applicable to treatments where serial critical structures with maximum dose constraint are located in or near the target. We studied intra-cranial tumors (high-grade meningiomas, base-of-skull chordomas) where the target (CTV) overlaps with the brainstem and optic structures. Often, high LETxD in critical structures can be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based re-optimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose

  8. National Energy Plan 2030: a proposal for power generation expansion in the long term; Plano Nacional de Energia 2030: uma proposta de expansao para a geracao de energia eletrica no longo prazo

    Energy Technology Data Exchange (ETDEWEB)

    Guerreiro, Amilcar Goncalves; Pereira Junior, Amaro Olimpio; Lopes, Juarez Castrillon; Tavares, Marina Elisabete E.; Silva, Renata de A.M. da; Queiroz, Renato P.; Oliveira, Ricardo G. de [Empresa de Pesquisa Energetica (EPE), Brasilia, DF (Brazil)

    2008-07-01

    The article aims to present and discuss a proposal for electric energy expansion generation capacity in long term. This work identifies the most appropriate evolution of the hydrothermal mix for the expansion of the supply of electrical power in the country, over the horizon of planning by 2030. (author)

  9. Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

    Science.gov (United States)

    Sukhikh, E.; Sheino, I.; Vertinsky, A.

    2017-09-01

    Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

  10. Treatment planning for heavy ion radiotherapy: calculation and optimization of biologically effective dose

    International Nuclear Information System (INIS)

    Kraemer, M.; Scholz, M.

    2000-09-01

    We describe a novel approach to treatment planning for heavy ion radiotherapy based on the local effect model (LEM) which allows to calculate the biologically effective dose not only for the target region but for the entire irradiation volume. LEM is ideally suited to be used as an integral part of treatment planning code systems for active dose shaping devices like the GSI raster scan system. Thus, it has been incorporated into our standard treatment planning system for ion therapy (TRiP). Single intensity modulated fields can be optimized with respect to homogeneous biologically effective dose. The relative biological effectiveness (RBE) is calculated separately for each voxel of the patient CT. Our radiobiologically oriented code system is in use since 1995 for the planning of irradiation experiments with cell cultures and animals such as rats and minipigs. Since 1997 it is in regular and successful use for patient treatment planning. (orig.)

  11. Optimization-based decision support to assist in logistics planning for hospital evacuations.

    Science.gov (United States)

    Glick, Roger; Bish, Douglas R; Agca, Esra

    2013-01-01

    The evacuation of the hospital is a very complex process and evacuation planning is an important part of a hospital's emergency management plan. There are numerous factors that affect the evacuation plan including the nature of threat, availability of resources and staff the characteristics of the evacuee population, and risk to patients and staff. The safety and health of patients is of fundamental importance, but safely moving patients to alternative care facilities while under threat is a very challenging task. This article describes the logistical issues and complexities involved in planning and execution of hospital evacuations. Furthermore, this article provides examples of how optimization-based decision support tools can help evacuation planners to better plan for complex evacuations by providing real-world solutions to various evacuation scenarios.

  12. Analysis of Various Multi-Objective Optimization Evolutionary Algorithms for Monte Carlo Treatment Planning System

    CERN Document Server

    Tydrichova, Magdalena

    2017-01-01

    In this project, various available multi-objective optimization evolutionary algorithms were compared considering their performance and distribution of solutions. The main goal was to select the most suitable algorithms for applications in cancer hadron therapy planning. For our purposes, a complex testing and analysis software was developed. Also, many conclusions and hypothesis have been done for the further research.

  13. Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

    Science.gov (United States)

    Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

    2015-01-01

    This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

  14. An adaptive dual-optimal path-planning technique for unmanned air vehicles

    Directory of Open Access Journals (Sweden)

    Whitfield Clifford A.

    2016-01-01

    Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.

  15. Optimal integration and test plans for software releases of lithographic systems

    NARCIS (Netherlands)

    Boumen, R.; Jong, de I.S.M.; Mortel - Fronczak, van de J.M.; Rooda, J.E.

    2007-01-01

    This paper describes a method to determine the optimal integration and test plan for embedded systems software releases. The method consists of four steps: 1)describe the integration and test problem in an integration and test model which is introduced in this paper, 2) determine possible test

  16. Prospective Teachers' Future Time Perspective and Professional Plans about Teaching: The Mediating Role of Academic Optimism

    Science.gov (United States)

    Eren, Altay

    2012-01-01

    This study aimed to examine the mediating role of prospective teachers' academic optimism in the relationship between their future time perspective and professional plans about teaching. A total of 396 prospective teachers voluntarily participated in the study. Correlation, regression, and structural equation modeling analyses were conducted in…

  17. Counting, enumerating and sampling of execution plans in a cost-based query optimizer

    NARCIS (Netherlands)

    F. Waas; C.A. Galindo-Legaria

    1999-01-01

    textabstractTesting an SQL database system by running large sets of deterministic or stochastic SQL statements is common practice in commercial database development. However, code defects often remain undetected as the query optimizer's choice of an execution plan is not only depending on

  18. Counting, Enumerating and Sampling of Execution Plans in a Cost-Based Query Optimizer

    NARCIS (Netherlands)

    F. Waas; C.A. Galindo-Legaria

    2000-01-01

    textabstractTesting an SQL database system by running large sets of deterministic or stochastic SQL statements is common practice in commercial database development. However, code defects often remain undetected as the query optimizer's choice of an execution plan is not only depending on the query

  19. Optimal, Risk-based Operation and Maintenance Planning for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard

    2008-01-01

    For offshore wind turbines costs to operation and maintenance are substantial. This paper describes a risk-based life-cycle approach for optimal planning of operation and maintenance. The approach is based on pre-posterior Bayesian decision theory. Deterioration mechanisms such as fatigue...

  20. Impact of using linear optimization models in dose planning for HDR brachytherapy

    International Nuclear Information System (INIS)

    Holm, Aasa; Larsson, Torbjoern; Carlsson Tedgren, Aasa

    2012-01-01

    Purpose: Dose plans generated with optimization models hitherto used in high-dose-rate (HDR) brachytherapy have shown a tendency to yield longer dwell times than manually optimized plans. Concern has been raised for the corresponding undesired hot spots, and various methods to mitigate these have been developed. The hypotheses upon this work is based are (a) that one cause for the long dwell times is the use of objective functions comprising simple linear penalties and (b) that alternative penalties, as these are piecewise linear, would lead to reduced length of individual dwell times. Methods: The characteristics of the linear penalties and the piecewise linear penalties are analyzed mathematically. Experimental comparisons between the two types of penalties are carried out retrospectively for a set of prostate cancer patients. Results: When the two types of penalties are compared, significant changes can be seen in the dwell times, while most dose-volume parameters do not differ significantly. On average, total dwell times were reduced by 4.2%, with a reduction of maximum dwell times by 25%, when the alternative penalties were used. Conclusions: The use of linear penalties in optimization models for HDR brachytherapy is one cause for the undesired long dwell times that arise in mathematically optimized plans. By introducing alternative penalties, a significant reduction in dwell times can be achieved for HDR brachytherapy dose plans. Although various measures for mitigating the long dwell times are already available, the observation that linear penalties contribute to their appearance is of fundamental interest.

  1. Mixed integer programming improves comprehensibility and plan quality in inverse optimization of prostate HDR Brachytherapy

    NARCIS (Netherlands)

    Gorissen, B.L.; den Hertog, D.; Hoffmann, A.L.

    2013-01-01

    Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or

  2. An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.

    Science.gov (United States)

    Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P

    2012-01-01

    The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example

  3. Optimized LTE Cell Planning with Varying Spatial and Temporal User Densities

    KAUST Repository

    Ghazzai, Hakim; Yaacoub, Elias; Alouini, Mohamed-Slim; Dawy, Zaher; Abu Dayya, Adnan

    2015-01-01

    Base station deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation (4G) cellular networks using meta-heuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterwards, we implement a meta-heuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently-proposed grey wolf optimizer) to find suboptimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regards to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality of service targets are always reached even for large-scale problems.

  4. Optimized LTE Cell Planning with Varying Spatial and Temporal User Densities

    KAUST Repository

    Ghazzai, Hakim

    2015-03-09

    Base station deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation (4G) cellular networks using meta-heuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterwards, we implement a meta-heuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently-proposed grey wolf optimizer) to find suboptimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regards to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality of service targets are always reached even for large-scale problems.

  5. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  6. Optimizing Maintenance Planning in the Production Industry Using the Markovian Approach

    Directory of Open Access Journals (Sweden)

    B Kareem

    2012-12-01

    Full Text Available Maintenance is an essential activity in every manufacturing establishment, as manufacturing effectiveness counts on the functionality of production equipment and machinery in terms of their productivity and operational life. Maintenance cost minimization can be achieved by adopting an appropriate maintenance planning policy. This paper applies the Markovian approach to maintenance planning decision, thereby generating optimal maintenance policy from the identified alternatives over a specified period of time. Markov chains, transition matrices, decision processes, and dynamic programming models were formulated for the decision problem related to maintenance operations of a cable production company. Preventive and corrective maintenance data based on workloads and costs, were collected from the company and utilized in this study. The result showed variability in the choice of optimal maintenance policy that was adopted in the case study. Post optimality analysis of the process buttressed the claim. The proposed approach is promising for solving the maintenance scheduling decision problems of the company.

  7. A particle swarm optimization algorithm for beam angle selection in intensity-modulated radiotherapy planning

    International Nuclear Information System (INIS)

    Li Yongjie; Yao Dezhong; Yao, Jonathan; Chen Wufan

    2005-01-01

    Automatic beam angle selection is an important but challenging problem for intensity-modulated radiation therapy (IMRT) planning. Though many efforts have been made, it is still not very satisfactory in clinical IMRT practice because of overextensive computation of the inverse problem. In this paper, a new technique named BASPSO (Beam Angle Selection with a Particle Swarm Optimization algorithm) is presented to improve the efficiency of the beam angle optimization problem. Originally developed as a tool for simulating social behaviour, the particle swarm optimization (PSO) algorithm is a relatively new population-based evolutionary optimization technique first introduced by Kennedy and Eberhart in 1995. In the proposed BASPSO, the beam angles are optimized using PSO by treating each beam configuration as a particle (individual), and the beam intensity maps for each beam configuration are optimized using the conjugate gradient (CG) algorithm. These two optimization processes are implemented iteratively. The performance of each individual is evaluated by a fitness value calculated with a physical objective function. A population of these individuals is evolved by cooperation and competition among the individuals themselves through generations. The optimization results of a simulated case with known optimal beam angles and two clinical cases (a prostate case and a head-and-neck case) show that PSO is valid and efficient and can speed up the beam angle optimization process. Furthermore, the performance comparisons based on the preliminary results indicate that, as a whole, the PSO-based algorithm seems to outperform, or at least compete with, the GA-based algorithm in computation time and robustness. In conclusion, the reported work suggested that the introduced PSO algorithm could act as a new promising solution to the beam angle optimization problem and potentially other optimization problems in IMRT, though further studies need to be investigated

  8. Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

    Science.gov (United States)

    Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

    2018-05-01

    Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

  9. Development of a Whole Body Atlas for Radiation Therapy Planning and Treatment Optimization

    International Nuclear Information System (INIS)

    Qatarneh, Sharif

    2006-01-01

    The main objective of radiation therapy is to obtain the highest possible probability of tumor cure while minimizing adverse reactions in healthy tissues. A crucial step in the treatment process is to determine the location and extent of the primary tumor and its loco regional lymphatic spread in relation to adjacent radiosensitive anatomical structures and organs at risk. These volumes must also be accurately delineated with respect to external anatomic reference points, preferably on surrounding bony structures. At the same time, it is essential to have the best possible physical and radiobiological knowledge about the radiation responsiveness of the target tissues and organs at risk in order to achieve a more accurate optimization of the treatment outcome. A computerized whole body Atlas has therefore been developed to serve as a dynamic database, with systematically integrated knowledge, comprising all necessary physical and radiobiological information about common target volumes and normal tissues. The Atlas also contains a database of segmented organs and a lymph node topography, which was based on the Visible Human dataset, to form standard reference geometry of organ systems. The reference knowledge base and the standard organ dataset can be utilized for Atlas-based image processing and analysis in radiation therapy planning and for biological optimization of the treatment outcome. Atlas-based segmentation procedures were utilized to transform the reference organ dataset of the Atlas into the geometry of individual patients. The anatomic organs and target volumes of the database can be converted by elastic transformation into those of the individual patient for final treatment planning. Furthermore, a database of reference treatment plans was started by implementing state-of-the-art biologically based radiation therapy planning techniques such as conformal, intensity modulated, and radio biologically optimized treatment planning. The computerized Atlas can

  10. Planning, Implementation and Optimization of Future space Missions using an Immersive Visualization Environement (IVE) Machine

    Science.gov (United States)

    Harris, E.

    Planning, Implementation and Optimization of Future Space Missions using an Immersive Visualization Environment (IVE) Machine E. N. Harris, Lockheed Martin Space Systems, Denver, CO and George.W. Morgenthaler, U. of Colorado at Boulder History: A team of 3-D engineering visualization experts at the Lockheed Martin Space Systems Company have developed innovative virtual prototyping simulation solutions for ground processing and real-time visualization of design and planning of aerospace missions over the past 6 years. At the University of Colorado, a team of 3-D visualization experts are developing the science of 3-D visualization and immersive visualization at the newly founded BP Center for Visualization, which began operations in October, 2001. (See IAF/IAA-01-13.2.09, "The Use of 3-D Immersive Visualization Environments (IVEs) to Plan Space Missions," G. A. Dorn and G. W. Morgenthaler.) Progressing from Today's 3-D Engineering Simulations to Tomorrow's 3-D IVE Mission Planning, Simulation and Optimization Techniques: 3-D (IVEs) and visualization simulation tools can be combined for efficient planning and design engineering of future aerospace exploration and commercial missions. This technology is currently being developed and will be demonstrated by Lockheed Martin in the (IVE) at the BP Center using virtual simulation for clearance checks, collision detection, ergonomics and reach-ability analyses to develop fabrication and processing flows for spacecraft and launch vehicle ground support operations and to optimize mission architecture and vehicle design subject to realistic constraints. Demonstrations: Immediate aerospace applications to be demonstrated include developing streamlined processing flows for Reusable Space Transportation Systems and Atlas Launch Vehicle operations and Mars Polar Lander visual work instructions. Long-range goals include future international human and robotic space exploration missions such as the development of a Mars

  11. Radiotherapy Planning Using an Improved Search Strategy in Particle Swarm Optimization.

    Science.gov (United States)

    Modiri, Arezoo; Gu, Xuejun; Hagan, Aaron M; Sawant, Amit

    2017-05-01

    Evolutionary stochastic global optimization algorithms are widely used in large-scale, nonconvex problems. However, enhancing the search efficiency and repeatability of these techniques often requires well-customized approaches. This study investigates one such approach. We use particle swarm optimization (PSO) algorithm to solve a 4D radiation therapy (RT) inverse planning problem, where the key idea is to use respiratory motion as an additional degree of freedom in lung cancer RT. The primary goal is to administer a lethal dose to the tumor target while sparing surrounding healthy tissue. Our optimization iteratively adjusts radiation fluence-weights for all beam apertures across all respiratory phases. We implement three PSO-based approaches: conventionally used unconstrained, hard-constrained, and our proposed virtual search. As proof of concept, five lung cancer patient cases are optimized over ten runs using each PSO approach. For comparison, a dynamically penalized likelihood (DPL) algorithm-a popular RT optimization technique is also implemented and used. The proposed technique significantly improves the robustness to random initialization while requiring fewer iteration cycles to converge across all cases. DPL manages to find the global optimum in 2 out of 5 RT cases over significantly more iterations. The proposed virtual search approach boosts the swarm search efficiency, and consequently, improves the optimization convergence rate and robustness for PSO. RT planning is a large-scale, nonconvex optimization problem, where finding optimal solutions in a clinically practical time is critical. Our proposed approach can potentially improve the optimization efficiency in similar time-sensitive problems.

  12. Penalized likelihood fluence optimization with evolutionary components for intensity modulated radiation therapy treatment planning

    International Nuclear Information System (INIS)

    Baydush, Alan H.; Marks, Lawrence B.; Das, Shiva K.

    2004-01-01

    A novel iterative penalized likelihood algorithm with evolutionary components for the optimization of beamlet fluences for intensity modulated radiation therapy (IMRT) is presented. This algorithm is designed to be flexible in terms of the objective function and automatically escalates dose, as long as the objective function increases and all constraints are met. For this study, the objective function employed was the product of target equivalent uniform dose (EUD) and fraction of target tissue within set homogeneity constraints. The likelihood component of the algorithm iteratively attempts to minimize the mean squared error between a homogeneous dose prescription and the actual target dose distribution. The updated beamlet fluences are then adjusted via a quadratic penalty function that is based on the dose-volume histogram (DVH) constraints of the organs at risk. The evolutionary components were included to prevent the algorithm from converging to a local maximum. The algorithm was applied to a prostate cancer dataset, with especially difficult DVH constraints on bladder, rectum, and femoral heads. Dose distributions were generated for manually selected sets of three-, four-, five-, and seven-field treatment plans. Additionally, a global search was performed to find the optimal orientations for an axial three-beam plan. The results from this optimal orientation set were compared to results for manually selected orientation (gantry angle) sets of 3- (0 deg., 90 deg., 270 deg. ), 4- (0 deg., 90 deg., 180 deg., 270 deg. ), 5- (0 deg., 50 deg., 130 deg., 230 deg., 310 deg.), and 7- (0 deg., 40 deg., 90 deg., 140 deg., 230 deg., 270 deg., 320 deg. ) field axial treatment plans. For all the plans generated, all DVH constraints were met and average optimization computation time was approximately 30 seconds. For the manually selected orientations, the algorithm was successful in providing a relatively homogeneous target dose distribution, while simultaneously satisfying

  13. Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    International Nuclear Information System (INIS)

    Thompson, S.A.; Fung, A.Y.C.; Zaider, M.

    2002-01-01

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results. (author)

  14. NOTE: Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    Science.gov (United States)

    Thompson, S. A.; Fung, A. Y. C.; Zaider, M.

    2002-08-01

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results.

  15. Optimal needle arrangement for intraoperative planning in permanent I-125 prostate implants

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, S.A. [Department of Medical Physics, North Shore-Long Island Jewish Health System, Manhassett, NY (United States); Fung, A.Y.C.; Zaider, M. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)

    2002-08-21

    One limitation of intraoperative planning of permanent prostate implants is that needles must already be in the gland before planning images are acquired. Improperly placed needles often restrict the capability of generating optimal seed placement. We developed guiding principles for the proper layout of needles within the treatment volume. The Memorial Sloan-Kettering Cancer Center planning system employs a genetic algorithm to find the optimal seed implantation pattern consistent with pre-assigned constraints (needle geometry, uniformity, conformity and the avoidance of high doses to urethra and rectum). Ultrasound volumes for twelve patients with I-125 implants were used to generate six plans per patient (total 72 plans) with different needle arrangements. The plans were evaluated in terms of V100 (percentage prostate volume receiving at least the prescription dose), U135 (percentage urethra volume receiving at least 135% of prescription dose), and CI (conformity index, the ratio of treatment volume to prescription dose volume.) The method termed POSTCTR, in which needles were placed on the periphery of the largest ultrasound slice and posterior central needles were placed as needed, consistently gave superior results for all prostate sizes. Another arrangement, labelled POSTLAT, where the needles were placed peripherally with additional needles in the posterior lateral lobes, also gave satisfactory results. We advocate two needle arrangements, POSTCTR and POSTLAT, with the former giving better results. (author)

  16. IPIP: A new approach to inverse planning for HDR brachytherapy by directly optimizing dosimetric indices

    International Nuclear Information System (INIS)

    Siauw, Timmy; Cunha, Adam; Atamtuerk, Alper; Hsu, I-Chow; Pouliot, Jean; Goldberg, Ken

    2011-01-01

    Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found. In this way, the dose distribution is controlled by abstract parameters. The purpose of this study is to develop a new approach for HDR brachytherapy by directly optimizing the dose distribution based on dosimetric criteria. Methods: The authors developed inverse planning by integer program (IPIP), an optimization model for computing HDR brachytherapy dose plans and a fast heuristic for it. They used their heuristic to compute dose plans for 20 anonymized prostate cancer image data sets from patients previously treated at their clinic database. Dosimetry was evaluated and compared to dosimetric criteria. Results: Dose plans computed from IPIP satisfied all given dosimetric criteria for the target and healthy tissue after a single iteration. The average target coverage was 95%. The average computation time for IPIP was 30.1 s on an Intel(R) Core TM 2 Duo CPU 1.67 GHz processor with 3 Gib RAM. Conclusions: IPIP is an HDR brachytherapy planning system that directly incorporates dosimetric criteria. The authors have demonstrated that IPIP has clinically acceptable performance for the prostate cases and dosimetric criteria used in this study, in both dosimetry and runtime. Further study is required to determine if IPIP performs well for a more general group of patients and dosimetric criteria, including other cancer sites such as GYN.

  17. A novel algorithm for solving optimal path planning problems based on parametrization method and fuzzy aggregation

    International Nuclear Information System (INIS)

    Zamirian, M.; Kamyad, A.V.; Farahi, M.H.

    2009-01-01

    In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.

  18. Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

    Science.gov (United States)

    Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

    2015-05-17

    The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of

  19. The time optimal trajectory planning with limitation of operating task for the Tokamak inspecting manipulator

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hesheng; Lai, Yinping [Department of Automation,Shanghai Jiao Tong University, Shanghai (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China (China); Chen, Weidong, E-mail: wdchen@sjtu.edu.cn [Department of Automation,Shanghai Jiao Tong University, Shanghai (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China (China)

    2016-12-15

    In this paper, a new optimization model of time optimal trajectory planning with limitation of operating task for the Tokamak inspecting manipulator is designed. The task of this manipulator is to inspect the components of Tokamak, the inspecting velocity of manipulator must be limited in the operating space in order to get the clear pictures. With the limitation of joint velocity, acceleration and jerk, this optimization model can not only get the minimum working time along a specific path, but also ensure the imaging quality of camera through the constraint of inspecting velocity. The upper bound of the scanning speed is not a constant but changes according to the observation distance of camera in real time. The relation between scanning velocity and observation distance is estimated by curve-fitting. Experiment has been carried out to verify the feasibility of optimization model, moreover, the Laplace image sharpness evaluation method is adopted to evaluate the quality of images obtained by the proposed method.

  20. Optimization-based guidelines to retirement planning and pension product design

    DEFF Research Database (Denmark)

    Konicz Bell, Agnieszka Karolina

    their retirement savings, this thesis presents some optimization techniques that could be applied by pension providers and financial advisers to provide individuals with such guidelines. For a given objective function and a number of constraints, we search for the optimal solution, which indicates, for example...... investigate the optimal annuity choice under inflation risk, which is often ignored both by practitioners advising on the retirement planning and by scholars investigating the consumption-investment problems. We search for an optimal level of retirement income in real terms, given investment opportunities...... in inflation-linked, nominal, and variable annuities, as well as in stocks and bonds. Our findings show that real annuities are a crucial asset in every portfolio, and that trying to hedge inflation without investing in inflation-linked products leads to a lower and more volatile retirement income. In the last...

  1. AngelStow: A Commercial Optimization-Based Decision Support Tool for Stowage Planning

    DEFF Research Database (Denmark)

    Delgado-Ortegon, Alberto; Jensen, Rune Møller; Guilbert, Nicolas

    save port fees, optimize use of vessel capacity, and reduce bunker consumption. Stowage Coordinators (SCs) produce these plans manually with the help of graphical tools, but high-quality SPs are hard to generate with the limited support they provide. In this abstract, we introduce AngelStow which...... is a commercial optimization-based decision support tool for stowing container vessels developed in collaboration between Ange Optimization and The IT University of Copenhagen. The tool assists SCs in the process of generating SPs interactively, focusing on satisfying and optimizing constraints and objectives...... that are tedious to deal with for humans, while letting the SCs use their expertise to deal with hard combinatorial objectives and corner cases....

  2. The time optimal trajectory planning with limitation of operating task for the Tokamak inspecting manipulator

    International Nuclear Information System (INIS)

    Wang, Hesheng; Lai, Yinping; Chen, Weidong

    2016-01-01

    In this paper, a new optimization model of time optimal trajectory planning with limitation of operating task for the Tokamak inspecting manipulator is designed. The task of this manipulator is to inspect the components of Tokamak, the inspecting velocity of manipulator must be limited in the operating space in order to get the clear pictures. With the limitation of joint velocity, acceleration and jerk, this optimization model can not only get the minimum working time along a specific path, but also ensure the imaging quality of camera through the constraint of inspecting velocity. The upper bound of the scanning speed is not a constant but changes according to the observation distance of camera in real time. The relation between scanning velocity and observation distance is estimated by curve-fitting. Experiment has been carried out to verify the feasibility of optimization model, moreover, the Laplace image sharpness evaluation method is adopted to evaluate the quality of images obtained by the proposed method.

  3. A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.

    Science.gov (United States)

    Gupta, Aparna; Li, Lepeng

    2004-05-01

    The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.

  4. Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

    Directory of Open Access Journals (Sweden)

    JingRui Zhang

    2015-03-01

    Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

  5. Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

    Science.gov (United States)

    Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

    2018-03-01

    The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

  6. An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles.

    Directory of Open Access Journals (Sweden)

    Yongjun Ahn

    Full Text Available The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive

  7. Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)

    Science.gov (United States)

    Xing, Lei; Li, Ruijiang

    2014-03-01

    The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.

  8. Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT)

    International Nuclear Information System (INIS)

    Xing, Lei; Li, Ruijiang

    2014-01-01

    The last few years have seen a number of technical and clinical advances which give rise to a need for innovations in dose optimization and delivery strategies. Technically, a new generation of digital linac has become available which offers features such as programmable motion between station parameters and high dose-rate Flattening Filter Free (FFF) beams. Current inverse planning methods are designed for traditional machines and cannot accommodate these features of new generation linacs without compromising either dose conformality and/or delivery efficiency. Furthermore, SBRT is becoming increasingly important, which elevates the need for more efficient delivery, improved dose distribution. Here we will give an overview of our recent work in SPORT designed to harness the digital linacs and highlight the essential components of SPORT. We will summarize the pros and cons of traditional beamlet-based optimization (BBO) and direct aperture optimization (DAO) and introduce a new type of algorithm, compressed sensing (CS)-based inverse planning, that is capable of automatically removing the redundant segments during optimization and providing a plan with high deliverability in the presence of a large number of station control points (potentially non-coplanar, non-isocentric, and even multi-isocenters). We show that CS-approach takes the interplay between planning and delivery into account and allows us to balance the dose optimality and delivery efficiency in a controlled way and, providing a viable framework to address various unmet demands of the new generation linacs. A few specific implementation strategies of SPORT in the forms of fixed-gantry and rotational arc delivery are also presented.

  9. An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles.

    Science.gov (United States)

    Ahn, Yongjun; Yeo, Hwasoo

    2015-01-01

    The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric

  10. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

    International Nuclear Information System (INIS)

    Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.; Heijmen, Ben J. M.

    2012-01-01

    Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions between patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Res