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Sample records for optimal expansion planning

  1. Transmission network expansion planning with simulation optimization

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Toole, G. Loren [Los Alamos National Laboratory

    2010-01-01

    Within the electric power literatW''e the transmi ssion expansion planning problem (TNEP) refers to the problem of how to upgrade an electric power network to meet future demands. As this problem is a complex, non-linear, and non-convex optimization problem, researchers have traditionally focused on approximate models. Often, their approaches are tightly coupled to the approximation choice. Until recently, these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (i.e. large amounts of limited control, renewable generation) that necessitates new optimization techniques. In this paper, we propose a generalization of the powerful Limited Discrepancy Search (LDS) that encapsulates the complexity in a black box that may be queJied for information about the quality of a proposed expansion. This allows the development of a new optimization algOlitlun that is independent of the underlying power model.

  2. Particle Swarm Optimization and Its Application in Transmission Network Expansion Planning

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The author introduced particle swarm optimization as a new method for power transmission network expansion planning. A new discrete method for particle swarm optimization, was developed, which is suitable for power transmission network expansion planning, and requires less computer s memory. The optimization fitness function construction, parameter selection, convergence judgement, and their characters were analyzed. Numerical simulation demonstrated the effectiveness and correctness of the method, This paper provides an academic and practical basis of particle swarm optimization in application of transmission network expansion planning for further investigation.

  3. Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Saraiva J. T.

    2012-10-01

    Full Text Available The basic objective of Transmission Expansion Planning (TEP is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.

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

    Energy Technology Data Exchange (ETDEWEB)

    Moghddas-Tafreshi, S.M. [Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Saliminia Lahiji, A. [Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran (Iran, Islamic Republic of); Rabiee, A. [Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Aghaei, J., E-mail: aghaei@iust.ac.i [Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz (Iran, Islamic Republic of)

    2011-02-15

    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.

  5. 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.

  6. A Novel Genetic-based Optimization for Transmission Constrained Generation Expansion Planning

    Directory of Open Access Journals (Sweden)

    Iman Goroohi Sardou

    2013-12-01

    Full Text Available Transmission constrained generation expansion planning (TC-GEP problem involves decisions on site, capacity, type of fuel, and etc. of new generation units, which should be installed over a planning horizon to meet the expectations of energy demand. This may lead to adding or lightening transmission lines congestion. This paper presents an application of genetic algorithm (GA to TC-GEP problem for simultaneously determination of new generation site, capacity and fuel type for a multi-period generation expansion plan. The objective function in this paper is to minimize the total generation cost which is composed of generation capital investment costs, operation and maintenance (O&M costs, outage cost, transmission losses costs and transmission enhancement costs. In this paper, also a new method is proposed for computing transmission enhancement costs. In addition a new approach is presented in this paper to determine site and number of combined cycle power plants regarding to candidate units. The GA is applied to solve TC-GEP problem for 4 bus test system from Grainger & Stevenson for a planning horizon of one year and the results are compared and validated against Enumeration Method (EM. Then GA is applied to solve TC-GEP problem for IEEE-RTS 24-bus test system for a planning horizon of three years and results are discussed.

  7. 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.

  8. 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.

  9. Urban underground network expansion planning

    Energy Technology Data Exchange (ETDEWEB)

    Bozic, Z. [Sinclair Knight Merz Pty Ltd., Perth (Australia); Hobson, E. [HI Consulting Services Pty Ltd., Adelaide (Australia)

    1997-03-01

    The authors describe a three step approach to expansion planning of high voltage (HV) urban underground distribution networks. Although the techniques are specifically oriented to underground systems, they are equally applicable to overhead system design. The fundamental engineering problem is how to connect individual high voltage to low voltage substations (HV/LV SS) and zone HV SS into a future urban underground network. The problem is to rearrange the HV network to minimise the cost of expansion subject to provision of an alternative supply, specified load transfer among the neighbouring zone SS, and other general planning constraints such as feeder capacity, voltage regulation, operational requirements and losses. A review of the current state of the art of distribution expansion planning is provided. The normal manual approach is discussed together with more recent research into computer methods. Three lines of computer research are identified and classified as radially constrained, security constrained and utilisation of travelling salesman/vehicle routing problem algorithms (TSP/VRP). The TSP/VRP line of research has been extended here to produce practical techniques for the assistance of network planners. (Author)

  10. Scalable and Practical Multi-Objective Distribution Network Expansion Planning

    NARCIS (Netherlands)

    Luong, N.H.; Grond, M.O.W.; La Poutré, 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

  11. Generation and transmission expansion planning for renewable energy integration

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Berscheid, Alan [Los Alamos National Laboratory; Toole, G. Loren [Los Alamos National Laboratory

    2010-11-30

    In recent years the expansion planning problem has become increasingly complex. As expansion planning (sometimes called composite or integrated resource planning) is a non-linear and non-convex optimization problem, researchers have traditionally focused on approximate models of power flows to solve the problem. The problem has also been split into generation expansion planning (GEP) and transmission network expansion planning (TNEP) to improve computational tractability. Until recently these approximations have produced results that are straight-forward to combine and adapt to the more complex and complete problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (e.g. large amounts of limited control, renewable generation, comparable generation and transmission construction costs) and necessitates new approaches. Recent work on deterministic Discrepancy Bounded Local Search (DBLS) has shown it to be quite effective in addressing the TNEP. In this paper, we propose a generalization of DBLS to handle simultaneous generation and transmission planning.

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

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Ding, Yi; Østergaard, Jacob

    2013-01-01

    Generation expansion planning (GEP) is the problem of finding the optimal strategy to plan the Construction of new generation while satisfying technical and economical constraints. In the deregulated and competitive environment, large-scale integration of wind generation (WG) in power system has...... 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...

  13. 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.

  14. 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

  15. Optimized $\\delta$ expansion for relativistic nuclear models

    CERN Document Server

    Krein, G I; Peres-Menezes, D; Nielsen, M; Pinto, M B

    1998-01-01

    The optimized $\\delta$-expansion is a nonperturbative approach for field theoretic models which combines the techniques of perturbation theory and the variational principle. This technique is discussed in the $\\lambda \\phi^4$ model and then implemented in the Walecka model for the equation of state of nuclear matter. The results obtained with the $\\delta$ expansion are compared with those obtained with the traditional mean field, relativistic Hartree and Hartree-Fock approximations.

  16. Transmission network expansion planning under deliberate outages

    Energy Technology Data Exchange (ETDEWEB)

    Alguacil, Natalia; Carrion, Miguel; Arroyo, Jose Manuel [E.T.S. de Ingenieros Industriales, Universidad de Castilla - La Mancha, Campus Universitario s/n, 13071 Ciudad Real (Spain)

    2009-10-15

    The reasons why the transmission network is a potentially attractive target for deliberate outages are twofold: (i) its crucial importance as a critical infrastructure for the society welfare, and (ii) its high level of vulnerability due to the current operation close to its static and dynamic limits. This new context where destructive agents come into play has been recognized by several agencies in Europe and North America, and various initiatives have been launched worldwide in order to assess and mitigate the vulnerability of transmission. Within this framework, this paper proposes the reinforcement and expansion of the transmission network as a way of mitigating the impact of increasingly plausible deliberate outages. The network planner selects the new lines to be built accounting not only for economic issues, as traditionally done, but also for the vulnerability of the transmission network against a set of credible intentional outages. The resulting vulnerability- and economic-constrained transmission expansion planning problem is formulated as a mixed-integer linear program. A number of case studies numerically illustrate the tradeoff between economic- and vulnerability-related issues and its impact on the expansion plans. In addition, we compare the results with those achieved by a traditional expansion planning model based on cost minimization. (author)

  17. Transmission Network Expansion Planning Considering Desired Generation Security

    Directory of Open Access Journals (Sweden)

    Samaneh GOLESTANI

    2014-02-01

    Full Text Available Transmission Network Expansion Planning (TNEP is an important part of power system planning in both conventional and new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Planning algorithm in this paper consisted of two stages. The former specifies highly uncertain lines and probability of congestion, considering desired generation security level (e.g. N-2 generation security level. The latter determines the optimal expansion capacity of existing lines. Splitting required capacity for reinforcement of weak lines due to desired generation security level simplifies the TNEP problem. In addition, it monitors the impact of generation uncertainty on transmission lines. Simulation results of the proposed idea are presented for IEEE-RTS-24bus network.

  18. 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

  19. Concepts for Integrated Planning of Port Capacity- Application to Rotterdam Expansion Plans

    Directory of Open Access Journals (Sweden)

    Sander Dekker

    2006-05-01

    Full Text Available Port planning is complicated due to many factors, includingthe existence of economies of scale in port expansion andthe fact that ports operate under competition. The port plannershould provide an overview of all potential strategies to enhanceport competitivness. Choices should be made with tailoreddesign concepts within a framework comprising supply-demand planning and cost-benefit analysis. Port expansionis a strategy to enhance port competitiveness and can be characterizedas a stmctural port capacity measure. Non-structuralalternatives comprise supply and demand management measuresand aim at efficient capacity utilization. In the design ofport expansion, a certain level of traffic congestion should beaccepted. Full integration of port-commercial and public interestsby combining structural and non-structural capacity measuresis essential for planning of port capacity. Efficiency, themain guiding principle for such planning, addresses the simultaneousdetermination of 1 optimal expansion size, and 2 investmentrecovery period.

  20. Considering DG in Expansion Planning of Subtransmission System

    Directory of Open Access Journals (Sweden)

    H. Shayeghi

    2011-01-01

    Full Text Available Deregulation has been obtained new options in the design and planning of the power system. One of these options is the integration of Distributed Generation (DG into the power system. In this paper, the presence of distributed generation is regarded as another alternative for supplying the load of subtransmission system. The effects of DG on expansion planning of subtransmission system have been modeled as an  optimization problem where the Genetic Algorithm (GA and Linear Programming (LP are employed to solve it. The proposed approach is applied to a realistic subtransmission system and the results are evaluated.

  1. 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.

  2. Global Optimization for Transport Network Expansion and Signal Setting

    Directory of Open Access Journals (Sweden)

    Haoxiang Liu

    2015-01-01

    Full Text Available 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 problems simultaneously. In this study, a combined network capacity expansion and signal setting model with consideration of vehicle queuing on approaching legs of intersection is developed to consider their mutual interactions so that best transport network performance can be guaranteed. We formulate the model as a bilevel program and design an approximated global optimization solution method based on mixed-integer linearization approach to solve the problem, which is inherently nnonlinear and nonconvex. Numerical experiments are conducted to demonstrate the model application and the efficiency of solution algorithm.

  3. 高速公路改扩建工程交通组织方案优化设计%An Optimal Design for Traffic Organization Plan of Highway Reconstruction and Expansion Projects

    Institute of Scientific and Technical Information of China (English)

    王晓; 杨少伟

    2011-01-01

    The features of the current road traffic organization methods are analyzed.Based on a study of the traffic situation on the Zhengzhou-Luohe Highway,a traffic organization plan during the reconstruction and expansion of the highway is designed and optimized.On the premise of road safety and unblocked traffic,this paper proposes a traffic organization implementation plan of the highway and an emergency management plan in the period of its reconstruction and expansion.%通过分析现有道路交通组织方式的特点,基于郑漯高速公路交通现状,介绍交通组织方案设计的基本思路,对郑漯高速公路改扩建期间交通组织方案进行设计和优选.在保证交通安全和道路畅通的前提下,提出郑漯高速公路改扩建期间的交通组织实施方案及改扩建期间的紧急事件处理方案.

  4. Extended Analytic Device Optimization Employing Asymptotic Expansion

    Science.gov (United States)

    Mackey, Jonathan; Sehirlioglu, Alp; Dynsys, Fred

    2013-01-01

    Analytic optimization of a thermoelectric junction often introduces several simplifying assumptionsincluding constant material properties, fixed known hot and cold shoe temperatures, and thermallyinsulated leg sides. In fact all of these simplifications will have an effect on device performance,ranging from negligible to significant depending on conditions. Numerical methods, such as FiniteElement Analysis or iterative techniques, are often used to perform more detailed analysis andaccount for these simplifications. While numerical methods may stand as a suitable solution scheme,they are weak in gaining physical understanding and only serve to optimize through iterativesearching techniques. Analytic and asymptotic expansion techniques can be used to solve thegoverning system of thermoelectric differential equations with fewer or less severe assumptionsthan the classic case. Analytic methods can provide meaningful closed form solutions and generatebetter physical understanding of the conditions for when simplifying assumptions may be valid.In obtaining the analytic solutions a set of dimensionless parameters, which characterize allthermoelectric couples, is formulated and provide the limiting cases for validating assumptions.Presentation includes optimization of both classic rectangular couples as well as practically andtheoretically interesting cylindrical couples using optimization parameters physically meaningful toa cylindrical couple. Solutions incorporate the physical behavior for i) thermal resistance of hot andcold shoes, ii) variable material properties with temperature, and iii) lateral heat transfer through legsides.

  5. Algorithm of capacity expansion on networks optimization

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The paper points out the relationship between the bottleneck and the minimum cutset of the network, and presents a capacity expansion algorithm of network optimization to solve the network bottleneck problem. The complexity of the algorithm is also analyzed. As required by the algorithm, some virtual sources are imported through the whole positive direction subsection in the network, in which a certain capacity value is given. Simultaneously, a corresponding capacity-expanded network is constructed to search all minimum cutsets. For a given maximum flow value of the network, the authors found an adjustment value of each minimum cutset arc's group with gradually reverse calculation and marked out the feasible flow on the capacity-extended networks again with the adjustment value increasing. All this has been done repeatedly until the original topology structure is resumed. So the algorithm can increase the capacity of networks effectively and solve the bottleneck problem of networks.

  6. Review of Power System Expansion Planning in Vietnam

    OpenAIRE

    Pereira, Mario

    2008-01-01

    This report assesses current energy expansion planning practices in Vietnam. This assessment comprises both technical aspects (methodology, planning criteria, construction of scenarios, sensitivity analysis and others) and evaluation of recent planning studies. In addition to an assessment of planning practices, it includes proposing a number of scenarios for the local consultant to carry ...

  7. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Foroud, Asghar Akbari; Abdoos, Ali Akbar; Keypour, Reza; Amirahmadi, Meisam [Electric and Computer Engineering Faculty, Semnan University, Semnan (Iran)

    2010-10-15

    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)

  9. Generation Expansion Planning with High Penetration of Wind Power

    Science.gov (United States)

    Sharan, Ishan; Balasubramanian, R.

    2016-08-01

    Worldwide thrust is being provided in generation of electricity from wind. Planning for the developmental needs of wind based power has to be consistent with the objective and basic framework of overall resource planning. The operational issues associated with the integration of wind power must be addressed at the planning stage. Lack of co-ordinated planning of wind turbine generators, conventional generating units and expansion of the transmission system may lead to curtailment of wind power due to transmission inadequacy or operational constraints. This paper presents a generation expansion planning model taking into account fuel transportation and power transmission constraints, while addressing the operational issues associated with the high penetration of wind power. For analyzing the operational issues, security constrained unit commitment algorithm is embedded in the integrated generation and transmission expansion planning model. The integrated generation and transmission expansion planning problem has been formulated as a mixed integer linear problem involving both binary and continuous variables in GAMS. The model has been applied to the expansion planning of a real system to illustrate the proposed approach.

  10. 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

  11. Multicriteria optimization informed VMAT planning.

    Science.gov (United States)

    Chen, Huixiao; Craft, David L; Gierga, David P

    2014-01-01

    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-IMRT or

  12. 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.

  13. Randomized discrepancy bounded local search for transmission expansion planning

    Energy Technology Data Exchange (ETDEWEB)

    Bent, Russell W [Los Alamos National Laboratory; Daniel, William B [Los Alamos National Laboratory

    2010-11-23

    In recent years the transmission network expansion planning problem (TNEP) has become increasingly complex. As the TNEP is a non-linear and non-convex optimization problem, researchers have traditionally focused on approximate models of power flows to solve the TNEP. Existing approaches are often tightly coupled to the approximation choice. Until recently these approximations have produced results that are straight-forward to adapt to the more complex (real) problem. However, the power grid is evolving towards a state where the adaptations are no longer easy (e.g. large amounts of limited control, renewable generation) and necessitates new approaches. Recent work on deterministic Discrepancy Bounded Local Search (DBLS) has shown it to be quite effective in addressing this question. DBLS encapsulates the complexity of power flow modeling in a black box that may be queried for information about the quality of proposed expansions. In this paper, we propose a randomization strategy that builds on DBLS and dramatically increases the computational efficiency of the algorithm.

  14. 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...

  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

    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...

  16. Variable Expansion Techniques for Decomposable Optimization Problems

    Science.gov (United States)

    2011-03-05

    meration or dynamic programming. Recall the edge partition problem studied by Taskin et al. above in reference 7. (Z. Caner Taskin was supported by the...Stochastic Integer Program- ming, August 2009 August 2009. 12 2. Z. Caner Taskin, Algorithms for Solving Multi-Level Optimization Problems with Dis

  17. 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.

  18. Optimization and capacity expansion of a water distribution system

    Science.gov (United States)

    Hsu, Nien-Sheng; Cheng, Wei-Chen; Cheng, Wen-Ming; Wei, Chih-Chiang; Yeh, William W.-G.

    2008-05-01

    This paper develops an iterative procedure for capacity expansion studies for water distribution systems. We propose a methodology to analyze an existing water distribution system and identify the potential bottlenecks in the system. Based on the results, capacity expansion alternatives are proposed and evaluated for improving the efficiency of water supply. The methodology includes a network flow based optimization model, four evaluation indices, and a series of evaluation steps. We first use a directed graph to configure the water distribution system into a network. The network flow based model optimizes the water distribution in the system so that different expansion alternatives can be evaluated on a comparable basis. This model lends itself to linear programming (LP) and can be easily solved by a standard LP code. The results from the evaluation tool help to identify the bottlenecks in the water distribution system and provide capacity expansion alternatives. A useful complementary tool for decision making is composed of a series of evaluation steps with the bottleneck findings, capacity expansion alternatives, and the evaluation of results. We apply the proposed methodology to the Tou-Qian River Basin, located in the northern region of Taiwan, to demonstrate its applicability in optimization and capacity expansion studies.

  19. 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.

  20. Risk Analysis for Resource Planning Optimization

    Science.gov (United States)

    Cheung, Kar-Ming

    2008-01-01

    This paper describes a systems engineering approach to resource planning by integrating mathematical modeling and constrained optimization, empirical simulation, and theoretical analysis techniques to generate an optimal task plan in the presence of uncertainties.

  1. Computational optimization techniques applied to microgrids planning

    DEFF Research Database (Denmark)

    Gamarra, Carlos; Guerrero, Josep M.

    2015-01-01

    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...

  2. Generation expansion planning in a competitive electric power industry

    Science.gov (United States)

    Chuang, Angela Shu-Woan

    This work investigates the application of non-cooperative game theory to generation expansion planning (GEP) in a competitive electricity industry. We identify fundamental ways competition changes the nature of GEP, review different models of oligopoly behavior, and argue that assumptions of the Cournot model are compatible with GEP. Applying Cournot theory of oligopoly behavior, we formulate a GEP model that may characterize expansion in the new competitive regime, particularly in pool-dominated generation supply industries. Our formulation incorporates multiple markets and is patterned after the basic design of the California ISO/PX system. Applying the model, we conduct numerical experiments on a test system, and analyze generation investment and market participation decisions of different candidate expansion units that vary in costs and forced outage rates. Simulations are performed under different scenarios of competition. In particular, we observe higher probabilistic measures of reliability from Cournot expansion compared to the expansion plan of a monopoly with an equivalent minimum reserve margin requirement. We prove several results for a subclass of problems encompassed by our formulation. In particular, we prove that under certain conditions Cournot competition leads to greater total capacity expansion than a situation in which generators collude in a cartel. We also show that industry output after introduction of new technology is no less than monopoly output. So a monopoly may lack sufficient incentive to introduce new technologies. Finally, we discuss the association between capacity payments and the issue of pricing reliability. And we derive a formula for computing ideal capacity payment rates by extending the Value of Service Reliability technique.

  3. 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)

  4. Distribution System Optimization Planning Based on Plant Growth Simulation Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Chun; CHENG Hao-zhong; HU Ze-chun; WANG Yi

    2008-01-01

    An approach for the integrated optimization of the construction/expansion capacity of high-voltage/medium-voltage (HV/MV) substations and the configuration of MV radial distribution network was presented using plant growth simulation algorithm (PGSA). In the optimization process, fixed costs correspondent to the investment in lines and substations and the variable costs associated to the operation of the system were considered under the constraints of branch capacity, substation capacity and bus voltage. The optimization variables considerably reduce the dimension of variables and speed up the process of optimizing. The effectiveness of the proposed approach was tested by a distribution system planning.

  5. 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...

  6. 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 thermal...... expansion, zero thermal expansion, and negative thermal expansion. Assuming linear elasticity, it is shown that materials with effective negative thermal expansion coefficients can be obtained by mixing two phases with positive thermal expansion coefficients and void. We also show...

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

    Directory of Open Access Journals (Sweden)

    Abass Samir A.

    2007-01-01

    Full Text Available 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. .

  8. An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning

    Institute of Scientific and Technical Information of China (English)

    Rongrit CHATTHAWORN; Surachai CHAITUSANEY

    2015-01-01

    We propose a new robust optimization approach to evaluate the impact of an intermittent renewable energy source on transmission expansion planning (TEP). The objective function of TEP is composed of the investment cost of the transmission line and the operating cost of conventional generators. A method to select suitable scenarios representing the intermittent renewable energy generation and loads is proposed to obtain robust expansion planning for all possible scenarios. A meta-heuristic algorithm called adaptive tabu search (ATS) is employed in the proposed TEP. ATS iterates between the main problem, which minimizes the investment and operating costs, and the subproblem, which minimizes the cost of power generation from conventional generators and curtailments of renewable energy generation and loads. The subproblem is solved by nonlinear programming (NLP) based on an interior point method. Moreover, the impact of an intermittent renewable energy source on TEP was evaluated by comparing expansion planning with and without consideration of a renewable energy source. The IEEE Reliability Test System 79 (RTS 79) was used for testing the proposed method and evaluating the impact of an intermittent renewable energy source on TEP. The results show that the proposed robust optimization approach provides a more robust solution than other methods and that the impact of an intermittent renewable energy source on TEP should be considered.

  9. An optimization framework for interdependent planning goals

    Science.gov (United States)

    Estlin, T. A.; Gaines, D. M.

    2002-01-01

    This paper describes an approach for optimizing over interdependent planning goals. We have implemented a methodology for representing and utilizing information about interdependent goals and their related utilities using the ASPEN planning and scheduling system.

  10. 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...

  11. Angelic Hierarchical Planning: Optimal and Online Algorithms

    Science.gov (United States)

    2008-12-06

    restrict our attention to plans in I∗(Act, s0). Definition 2. ( Parr and Russell , 1998) A plan ah∗ is hierarchically optimal iff ah∗ = argmina∈I∗(Act,s0):T...Murdock, Dan Wu, and Fusun Yaman. SHOP2: An HTN planning system. JAIR, 20:379–404, 2003. Ronald Parr and Stuart Russell . Reinforcement Learning with...Angelic Hierarchical Planning: Optimal and Online Algorithms Bhaskara Marthi Stuart J. Russell Jason Wolfe Electrical Engineering and Computer

  12. Optical transfer function optimization based on linear expansions

    Science.gov (United States)

    Schwiegerling, Jim

    2015-09-01

    The Optical Transfer Function (OTF) and its modulus the Modulation Transfer Function (MTF) are metrics of optical system performance. However in system optimization, calculation times for the OTF are often substantially longer than more traditional optimization targets such as wavefront error or transverse ray error. The OTF is typically calculated as either the autocorrelation of the complex pupil function or as the Fourier transform of the Point Spread Function. We recently demonstrated that the on-axis OTF can be represented as a linear combination of analytical functions where the weighting terms are directly related to the wavefront error coefficients and apodization of the complex pupil function. Here, we extend this technique to the off-axis case. The expansion technique offers a potential for accelerating OTF optimization in lens design, as well as insight into the interaction of aberrations with components of the OTF.

  13. 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.

  14. Multiobjective transmission expansion planning considering security and demand uncertainty

    Directory of Open Access Journals (Sweden)

    Ricardo Andrés Bolaños Ocampo

    2010-05-01

    Full Text Available This paper presents a methodology for resolving the transmission expansion planning problem by considering single contingency criteria (N-1. Each bus bar in the power system considered future demand uncertainty. The planning problem was divided into an investment problem (calculating investment costs and an operative problem (resolving power flows. A modified evolutionary elitist non-dominated sorted genetic algorithm (NSGA-II was used for resolving the investment problem, determining several in- vestment proposals where feasibility was evaluated by solving the operative problem. On the other hand, a high order interior point (HOIP method was proposed for solving load flow problems. The methodology was tested by using two systems found in the specialised literature: IEEE-24 bus and Garver or IEEE-6 bus systems. The results, when compared with traditional ones, sho- wed the proposed method’s power and the multi-objective technique’s convenience.

  15. Optimal Placement and Sizing of FACTS Devices to Delay Transmission Expansion

    CERN Document Server

    Frolov, Vladimir; Backhaus, Scott; Bialek, Janusz; Chertkov, Michael

    2016-01-01

    The Transmission System Operators (TSOs) plan to reinforce their transmission grids based on the projected system congestion caused by the increase in future system load, amongst other factors. However, transmission expansion is severely limited in many countries, and especially in Europe, due to many factors such as clearance acquisitions. An alternative is to use Flexible Alternating Current Transmission System (FACTS) devices, thus allowing to delay or avoid much more expensive transmission expansion. These devices are capable of utilizing the existing transmission grid more flexibly. However, the locations and sizing of future FACTS devices must be carefully determined during the planning phase in order to avoid congestion under many representative scenarios of the projected economic growth (of loads). This paper proposes an optimization approach, based on AC Power Flows, to determine suitable locations and sizes of series and shunt FACTS devices. Non-linear, non-convex and multiple-scenario based optimiz...

  16. 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.

  17. Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning.

    Science.gov (United States)

    Luong, Ngoc Hoang; Poutré, Han La; Bosman, Peter A N

    2017-04-07

    This article tackles the Distribution Network Expansion Planning (DNEP) problemthat has to be solved by distribution network operators to decide which, where, and/or when enhancements to electricity networks should be introduced to satisfy the future power demands. Because of many real-world details involved, the structure of the problem is not exploited easily using mathematical programming techniques, for which reason we consider solving this problem with evolutionary algorithms (EAs). We compare three types of EAs for optimizing expansion plans: the classic genetic algorithm (GA), the estimation-of-distribution algorithm (EDA), and the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA). Not fully knowing the structure of the problem, we study the effect of linkage learning through the use of three linkage models: univariate, marginal product, and linkage tree. We furthermore experiment with the impact of incorporating different levels of problem-specific knowledge in the variation operators. Experiments show that the use of problem-specific variation operators is far more important for the classic GA to find high-quality solutions. In all EAs, the marginal product model and its linkage learning procedure have difficulty in capturing and exploiting the DNEP problemstructure. GOMEA, especiallywhen combined with the linkage tree structure, is found to have the most robust performance by far, even when an out-of-the-box variant is used that does not exploit problem-specific knowledge. Based on experiments, we suggest that when selecting optimization algorithms for power system expansion planning problems, EAs that have the ability to effectively model and efficiently exploit problem structures, such as GOMEA, should be given priority, especially in the case of black-box or grey-box optimization.

  18. [Implementation and expansion of family planning services: questions and controversies].

    Science.gov (United States)

    Canesqui, A M

    1985-01-01

    Even though the Brazilian government's position on birth control in the last few years has been ambiguous, it is moving away from the pro-life attitude that was prevalent in the 1960s and through the mid-1970s. The economic conditions during this period created a sense of urgency in establishing family planning programs to divert possible economic and social repercussions. The creation and expansion of family planning services in the last 2 decades have improved the distribution of contraceptives, related health care, and research. The problems of birth control and family planning are the same in Brazil as in the rest of the world. There is and always will be a moral, ethical, religious, or political question from the groups that traditionally oppose these concepts. The theme of responsible birth control is 1 of the tools used in the attempt to get the message across. Some results of irresponsible birth control are abortions, poverty, and misery. Proposals for integrating the various family planning services have not been implemented due to a lack of priorities in spending the available funds. Most of these health groups place responsibility for providing these methods of family planning upon the State. The groups say the State needs to consider women's freedom, sexuality and personal preferences in providing the family planning programs. A few groups prefer private sector sponsorship in order to preserve the woman's options concerning health care. The need for health care and the question of democracy both need to be taken into consideration when dealing with human reproduction. Attention should also be paid to the quality of health service, in order to guarantee less distortion of the issue and provide better medical care for all.

  19. 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)

  20. Production Planning Based on BOM Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    According to a prototype enterprise, a rulebased Bill of Materials (BOM) structure is designed in order to get optimal design and management of product BOM. The constraint rules and optional objects for product data structure optimization are considered by associating customer demands with product BOM. Furthermore, the functional model of production planning system for assembling enterprise is given based on customization and BOM optimization.

  1. 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 of these infrast......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...... of these infrastructures using conversion technologies (e.g. gas-to-electricity-and-heat, power-to-heat, power-to-gas), and the placement of energy storage. The model is demonstrated using a representative case study from the city of Eindhoven. Current energy data from 2015 is combined with city development scenarios...... 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...

  2. Software for Optimizing Plans Involving Interdependent Goals

    Science.gov (United States)

    Estlin, Tara; Gaines, Daniel; Rabideau, Gregg

    2005-01-01

    A computer program enables construction and optimization of plans for activities that are directed toward achievement of goals that are interdependent. Goal interdependence is defined as the achievement of one or more goals affecting the desirability or priority of achieving one or more other goals. This program is overlaid on the Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been described in a number of prior NASA Tech Briefs articles. Unlike other known or related planning programs, this program considers interdependences among goals that can change between problems and provides a language for easily specifying such dependences. Specifications of the interdependences can be formulated dynamically and provided to the associated planning software as part of the goal input. Then an optimization algorithm provided by this program enables the planning software to reason about the interdependences and incorporate them into an overall objective function that it uses to rate the quality of a plan under construction and to direct its optimization search. In tests on a series of problems of planning geological experiments by a team of instrumented robotic vehicles (rovers) on new terrain, this program was found to enhance plan quality.

  3. OPTIMAL TRAJECTORY PLANNING OF MANIPULATORS: A REVIEW

    Directory of Open Access Journals (Sweden)

    ATEF A. ATA

    2007-04-01

    Full Text Available Optimal motion planning is very important to the operation of robot manipulators. Its main target is the generation of a trajectory from start to goal that satisfies objectives, such as minimizing path traveling distance or time interval, lowest energy consumption or obstacle avoidance and satisfying the robot’s kinematics and dynamics. Review, discussion and analysis of optimization techniques to find the optimal trajectory either in Cartesian space or joint space are presented and investigated. Optimal trajectory selection approaches such as kinematics and dynamics techniques with various constraints are presented and explained. Although the kinematics approach is simple and straight forward, it will experience some problems in implementation because of lack of Inertia and torque constraints. The application of Genetic Algorithms to find the optimal trajectory of manipulators especially in the obstacle avoidance is also highlighted. Combining the Genetic Algorithms with other classical optimization methods proves to have better performance as a hybrid optimization technique.

  4. Enterprise resource planning implementation decision & optimization models

    Institute of Scientific and Technical Information of China (English)

    Wang Shaojun; Wang Gang; Lü Min; Gao Guoan

    2008-01-01

    To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review technique (PERT), some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.

  5. 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

  6. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Sadegheih, A. [Department of Industrial Engineering, University of Yazd, P.O. Box 89195-741, Yazd (Iran); Drake, P.R. [E-Business and Operations Management Division, University of Liverpool Management School, University of Liverpool, Liverpool (United Kingdom)

    2008-06-15

    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. (author)

  8. SURFACE MINE PLANNING OPTIMIZATION BY GOAL PROGRAMMING

    Institute of Scientific and Technical Information of China (English)

    陈意平; 张幼蒂

    1991-01-01

    This paper introduced an approach to surface mine planning optimization-Goal Programming.The multiobjective[0-1] model has been built and the software has been developed.The method has been applied to a huge surface coal mine,the result of which shows that it is effective and feasible.

  9. An Enhanced Genetic Algorithm to Solve the Static and Multistage Transmission Network Expansion Planning

    Directory of Open Access Journals (Sweden)

    Luis A. Gallego

    2012-01-01

    Full Text Available An enhanced genetic algorithm (EGA is applied to solve the long-term transmission expansion planning (LTTEP problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1 generation of an initial population using fast, efficient heuristic algorithms, (2 better implementation of the local improvement phase and (3 efficient solution of linear programming problems (LPs. Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem.

  10. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    Alishahi, Ehsan [Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-143 (Iran, Islamic Republic of); Moghaddam, Mohsen P., E-mail: parsa@modares.ac.ir [Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-143 (Iran, Islamic Republic of); Sheikh-El-Eslami, Mohammad K. [Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, P.O. Box 14115-143 (Iran, Islamic Republic of)

    2011-08-15

    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.

  12. Optimal planning of high voltage distribution substations

    Institute of Scientific and Technical Information of China (English)

    YU Yixin; YAN Xuefei; ZHANG Yongwu

    2007-01-01

    Aimed at solving the problem of optimal planning for high voltage distribution substations,an efficient method is put forward.The method divides the problem into two sub-problems:source locating and combinational optimization.The algorithm of allocating and locating alternatively (ALA) is widely used to deal with the source locating problem,but it is dependent on the initial location to a large degree.Thus,some modifications were made to the ALA algorithm,which could greatly improve the quality of solutions.In addition,considering the non-convex and nonconcave nature of the sub-problem of combinational optimization,the branch-and-bound technique was adopted to obtain or approximate a global optimal solution.To improve the efficiency of the branch-and-bound technique,some heuristic principles were proposed to cut those branches that may generate a global optimization solution with low probability.Examples show that the proposed algorithm meets the requirement of engineering and it is an effective approach to rapidly solve the problem of optimal planning for high voltage distribution substations.

  13. Fast and accurate sensitivity analysis of IMPT treatment plans using Polynomial Chaos Expansion

    Science.gov (United States)

    Perkó, Zoltán; van der Voort, Sebastian R.; van de Water, Steven; Hartman, Charlotte M. H.; Hoogeman, Mischa; Lathouwers, Danny

    2016-06-01

    The highly conformal planned dose distribution achievable in intensity modulated proton therapy (IMPT) can severely be compromised by uncertainties in patient setup and proton range. While several robust optimization approaches have been presented to address this issue, appropriate methods to accurately estimate the robustness of treatment plans are still lacking. To fill this gap we present Polynomial Chaos Expansion (PCE) techniques which are easily applicable and create a meta-model of the dose engine by approximating the dose in every voxel with multidimensional polynomials. This Polynomial Chaos (PC) model can be built in an automated fashion relatively cheaply and subsequently it can be used to perform comprehensive robustness analysis. We adapted PC to provide among others the expected dose, the dose variance, accurate probability distribution of dose-volume histogram (DVH) metrics (e.g. minimum tumor or maximum organ dose), exact bandwidths of DVHs, and to separate the effects of random and systematic errors. We present the outcome of our verification experiments based on 6 head-and-neck (HN) patients, and exemplify the usefulness of PCE by comparing a robust and a non-robust treatment plan for a selected HN case. The results suggest that PCE is highly valuable for both research and clinical applications.

  14. Optimization approaches for planning external beam radiotherapy

    Science.gov (United States)

    Gozbasi, Halil Ozan

    Cancer begins when cells grow out of control as a result of damage to their DNA. These abnormal cells can invade healthy tissue and form tumors in various parts of the body. Chemotherapy, immunotherapy, surgery and radiotherapy are the most common treatment methods for cancer. According to American Cancer Society about half of the cancer patients receive a form of radiation therapy at some stage. External beam radiotherapy is delivered from outside the body and aimed at cancer cells to damage their DNA making them unable to divide and reproduce. The beams travel through the body and may damage nearby healthy tissue unless carefully planned. Therefore, the goal of treatment plan optimization is to find the best system parameters to deliver sufficient dose to target structures while avoiding damage to healthy tissue. This thesis investigates optimization approaches for two external beam radiation therapy techniques: Intensity-Modulated Radiation Therapy (IMRT) and Volumetric-Modulated Arc Therapy (VMAT). We develop automated treatment planning technology for IMRT that produces several high-quality treatment plans satisfying provided clinical requirements in a single invocation and without human guidance. A novel bi-criteria scoring based beam selection algorithm is part of the planning system and produces better plans compared to those produced using a well-known scoring-based algorithm. Our algorithm is very efficient and finds the beam configuration at least ten times faster than an exact integer programming approach. Solution times range from 2 minutes to 15 minutes which is clinically acceptable. With certain cancers, especially lung cancer, a patient's anatomy changes during treatment. These anatomical changes need to be considered in treatment planning. Fortunately, recent advances in imaging technology can provide multiple images of the treatment region taken at different points of the breathing cycle, and deformable image registration algorithms can

  15. Expansion of cooperatively growing populations: Optimal migration rates and habitat network structures

    Science.gov (United States)

    Yang, Kai-Cheng; Wu, Zhi-Xi; Holme, Petter; Nonaka, Etsuko

    2017-01-01

    Range expansion of species is driven by the interactions among individual- and population-level processes and the spatial pattern of habitats. In this work we study how cooperatively growing populations spread on networks representing the skeleton of complex landscapes. By separating the slow and fast variables of the expansion process, we are able to give analytical predictions for the critical conditions that divide the dynamic behaviors into different phases (extinction, localized survival, and global expansion). We observe a resonance phenomenon in how the critical condition depends on the expansion rate, indicating the existence of an optimal strategy for global expansion. We derive the conditions for such optimal migration in locally treelike graphs and numerically study other structured networks. Our results highlight the importance of both the underlying interaction pattern and migration rate of the expanding populations for range expansion. We also discuss potential applications of the results to biological control and conservation.

  16. 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.

  17. GPU-based ultrafast IMRT plan optimization

    Science.gov (United States)

    Men, Chunhua; Gu, Xuejun; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B.

    2009-11-01

    The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California, San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evaluate our implementation. On an NVIDIA Tesla C1060 GPU card, we have achieved speedup factors of 20-40 without losing accuracy, compared to the results from an Intel Xeon 2.27 GHz CPU. For a specific nine-field prostate IMRT case with 5 × 5 mm2 beamlet size and 2.5 × 2.5 × 2.5 mm3 voxel size, our GPU implementation takes only 2.8 s to generate an optimal IMRT plan. Our work has therefore solved a major problem in developing online re-planning technologies for adaptive radiotherapy.

  18. Optimization of Heat-Sink Cooling Structure in EAST with Hydraulic Expansion Technique%Optimization of Heat-Sink Cooling Structure in EAST with Hydraulic Expansion Technique

    Institute of Scientific and Technical Information of China (English)

    许铁军; 黄生洪; 谢韩; 宋云涛; 张平; 戢翔; 高大明

    2011-01-01

    Considering utilization of the original chromium-bronze material, two processing techniques including hydraulic expansion and high temperature vacuum welding were proposed for the optimization of heat-sink structure in EAST. The heat transfer performance of heat-sink with or without cooling tube was calculated and different types of connection between tube and heat-sink were compared by conducting a special test. It is shown from numerical analysis that the diameter of heat-sink channel can be reduced from 12 mm to 10 mm. Compared with the original sample, the thermal contact resistance between tube and heat-sink for welding sample can reduce the heat transfer performance by 10%, while by 20% for the hydraulic expansion sample. However, the welding technique is more complicated and expensive than hydraulic expansion technique. Both the processing technique and the heat transfer performance of heat-sink prototype should be further considered for the optimization of heat-sink structure in EAST.

  19. Land Protection Plan: Rocky Mountain Front Conservation Area Expansion

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This Land Protection Plan for Rocky Mountain Front Conservation Area provides a description of the project, a description of the area and its resources, threats to...

  20. Land Protection Plan: Rainwater Basin Wetland Management District Expansion

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This Land Protection Plan (LLP) describes the priorities for acquiring additional acres within the boundary of the Rainwater Basin Wetland Management District. The...

  1. 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.

  2. 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.

  3. Optimal Planning and Problem-Solving

    Science.gov (United States)

    Clemet, Bradley; Schaffer, Steven; Rabideau, Gregg

    2008-01-01

    CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

  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

    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.

  5. 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

  6. 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.

  7. 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.

  8. Capricious Cables: Understanding the Key Concepts in Transmission Expansion Planning and Its Models

    Energy Technology Data Exchange (ETDEWEB)

    Donohoo, P.; Milligan, M.

    2014-06-01

    The extra-high-voltage transmission network is the bulk transport network of the electric power system. To understand how the future power system may react to planning decisions today, wide-area transmission models are increasingly used to aid decision makers and stakeholders. The goal of this work is to illuminate these models for a broader audience that may include policy makers or relative newcomers to the field of transmission planning. This paper explains the basic transmission expansion planning model formulation. It highlights six of the major simplifications made in transmission expansion planning models and the resulting need to contextualize model results using knowledge from other models and knowledge not captured in the modeling process.

  9. Exploiting linkage information and problem-specific knowledge in evolutionary distribution network expansion planning

    NARCIS (Netherlands)

    N.H. Luong (Ngoc Hoang); J.A. La Poutré (Han); P.A.N. Bosman (Peter)

    2017-01-01

    textabstractThis article tackles the Distribution Network Expansion Planning (DNEP) problem that has to be solved by distribution network operators to decide which, where, and/or when enhancements to electricity networks should be introd uced to satisfy the future power demands. Because of many

  10. Analog Ensemble Methodology: Expansion and Optimization for Renewable Energy Applications

    Science.gov (United States)

    Harding, L.; Cervone, G.; Delle Monache, L.

    2015-12-01

    Renewable energy is fundamental for sustaining and developing society. Solar and wind energy are promising sources because of their decreased environmental impact relative to conventional energy sources, improved efficiency, and increased use. A key challenge with renewable energy production is the generation of accurate renewable energy forecasts at varying spatial and temporal scales to assist utility companies in effective energy management. Specifically, this research applies the Analog Ensemble (AnEn) methodology to short-term (0-48 hour) wind speed forecasting for power generation and short-term (0-72) hour solar power measured (PM) output predictions. AnEn uses a set of past observations corresponding to the best analogs of a deterministic numerical weather prediction model to generate a probability distribution of future atmospheric states: an ensemble of analogs. Currently the AnEn methodology equally weights predictors and only handles 1D(time). We determine an optimal distribution of predictor weights based upon parameter characteristics, investigate spatial variations in the application of the methodology and develop a theory expanding the methodology into 2D. The AnEn methodology improves short-term prediction accuracy, decreases computational costs and provides uncertainty quantification allowing utility companies to manage over- or under power generation for renewable energy sources.

  11. Sub-optimality analysis of mobile robot rolling path planning

    Institute of Scientific and Technical Information of China (English)

    张纯刚; 席裕庚

    2003-01-01

    Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.

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

    Institute of Scientific and Technical Information of China (English)

    曹瑞芬; 吴宜灿; 裴曦; 景佳; 李国丽; 程梦云; 李贵; 胡丽琴

    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 pl

  13. Grasslands Wildlife Management Area proposed expansion: Environmental Assessment, Land Protection Plan, and Conceptual Management Plan

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This document discusses the proposed expansion of the Service's easement program for protection of the wildlife habitat of Merced County's Grasslands Ecological...

  14. Simulation of stochastic systems via polynomial chaos expansions and convex optimization

    CERN Document Server

    Fagiano, Lorenzo

    2012-01-01

    Polynomial Chaos Expansions represent a powerful tool to simulate stochastic models of dynamical systems. Yet, deriving the expansion's coefficients for complex systems might require a significant and non-trivial manipulation of the model, or the computation of large numbers of simulation runs, rendering the approach too time consuming and impracticable for applications with more than a handful of random variables. We introduce a novel computationally tractable technique for computing the coefficients of polynomial chaos expansions. The approach exploits a regularization technique with a particular choice of weighting matrices, which allow to take into account the specific features of Polynomial Chaos expansions. The method, completely based on convex optimization, can be applied to problems with a large number of random variables and uses a modest number of Monte Carlo simulations, while avoiding model manipulations. Additional information on the stochastic process, when available, can be also incorporated i...

  15. Assessment of a methodology for transmission expansion planning around the North Sea

    Energy Technology Data Exchange (ETDEWEB)

    Jaehnert, Stefan; Farahmand, Hossein; Voeller, Steve; Wolfgang, Ove; Huertas-Hernando, Daniel [SINTEF Energy Research, Trondheim (Norway)

    2012-07-01

    The expected increase of wind power production in the North Sea area requires the access to resources of flexible power production. Since the Nordic hydro-based power system can provide such resources, a stronger interconnection between continental Europe and the Nordic is required. Transmission expansion planning is necessary to assess the benefit of potential new transmission lines. A transmission expansion methodology is presented in this paper. The methodology is based on merchant lines and is applied to a 2030 scenario of the Northern European power system. (orig.)

  16. The Decenal Plan for the expansion of electric power (PDEE); O Plano Decenal de expansao de energia eletrica (PDEE)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    This chapter covers the following aspects of the Decenal Plan for the expansion of electric power: general directives; methodology - criteria and procedures; planning of the generation - criteria and procedures; planning of the transmission - criteria and procedures; integrated socio environmental analysis of the Plan.

  17. 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

  18. 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

  19. Optimal Reliability-Based Planning of Experiments for POD Curves

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.

    Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...

  20. 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.

  1. 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.

  2. Optimal Reliability-Based Planning of Experiments for POD Curves

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; Kroon, I. B.

    Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First O...... Order Reliability Methods in combination with life-cycle cost-optimal inspection and maintenance planning. The methodology is based on preposterior analyses from Bayesian decision theory. An illustrative example is shown.......Optimal planning of the crack detection test is considered. The test are used to update the information on the reliability of the inspection techniques modelled by probability of detection (P.O.D.) curves. It is shown how cost-optimal and reliability based test plans can be obtained using First...

  3. Optimal Road Capacity Building : Road Planning by Marginal Cost Pricing

    OpenAIRE

    NEMOTO, Toshinori; Misui, Yuki; Kajiwara, Akira

    2009-01-01

    The purpose of this study is to propose a new road planning and financing scheme based on short-term social marginal cost pricing that facilitates the establishment of optimal road standards in the long term. We conducted a simulation analysis based on the proposed planning scheme and observed that the simulation calculated the optimal road capacity in the future, and thus proved that the new planning scheme is feasible.

  4. 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

  5. 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

  6. 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

  7. [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.

  8. Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy.

    Science.gov (United States)

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

    2012-01-01

    To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT). 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. 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. 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. Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Implications of capacity expansion under uncertainty and value of information: The near-term energy planning of Japan

    Energy Technology Data Exchange (ETDEWEB)

    Krukanont, Pongsak [Energy Economics Laboratory, Department of Socio-Environmental Energy Science, Graduate School of Energy Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan); Tezuka, Tetsuo [Energy Economics Laboratory, Department of Socio-Environmental Energy Science, Graduate School of Energy Science, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)]. E-mail: tezuka@energy.kyoto-u.ac.jp

    2007-10-15

    In this paper, we present the near-term analysis of capacity expansion under various uncertainties from the viewpoints of the decision-making process on the optimal allocation of investment and the value of information. An optimization model based on two-stage stochastic programming was developed using real data to describe the Japanese energy system as a case study. Different uncertainty parameters were taken into consideration by a disaggregate analysis of a bottom-up energy modeling approach, including end-use energy demands, plant operating availability and carbon tax rate. Four policy regimes represented as energy planning or policy options were also studied, covering business as usual, renewable energy target, carbon taxation and nuclear phase-out regimes. In addition, we investigated the role of various energy technologies and the behavior of the value of information with respect to the probability function of the worst-case scenario. This value of information provides decision makers with a quantitative analysis for the cost to obtain perfect information about the future. The developed model could be regarded as an applicable tool for decision support to provide a better understanding in energy planning and policy analyses.

  10. 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...... 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......, 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...

  11. 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

  12. Modeling to Optimize Hospital Evacuation Planning in EMS Systems.

    Science.gov (United States)

    Bish, Douglas R; Tarhini, Hussein; Amara, Roel; Zoraster, Richard; Bosson, Nichole; Gausche-Hill, Marianne

    2017-01-01

    To develop optimal hospital evacuation plans within a large urban EMS system using a novel evacuation planning model and a realistic hospital evacuation scenario, and to illustrate the ways in which a decision support model may be useful in evacuation planning. An optimization model was used to produce detailed evacuation plans given the number and type of patients in the evacuating hospital, resource levels (teams to move patients, vehicles, and beds at other hospitals), and evacuation rules. Optimal evacuation plans under various resource levels and rules were developed and high-level metrics were calculated, including evacuation duration and the utilization of resources. Using this model we were able to determine the limiting resources and demonstrate how strategically augmenting the resource levels can improve the performance of the evacuation plan. The model allowed the planner to test various evacuation conditions and resource levels to demonstrate the effect on performance of the evacuation plan. We present a hospital evacuation planning analysis for a hospital in a large urban EMS system using an optimization model. This model can be used by EMS administrators and medical directors to guide planning decisions and provide a better understanding of various resource allocation decisions and rules that govern a hospital evacuation.

  13. Model-based Optimal Evacuation Planning anticipating Traveler Compliance Behavior

    NARCIS (Netherlands)

    Pel, A.J.; Huibregtse, O.L.; Hoogendoorn, S.P.; Bliemer, M.C.J.

    2010-01-01

    Instructing evacuees on their departure time, destination, and route can lead to more efficient evacuation traffic operations. While current evacuation plan optimization techniques are limited to assessing mandatory evacuation where travelers strictly follow the instructions, in reality a share of

  14. Optimization of energy planning strategies in municipalities

    DEFF Research Database (Denmark)

    Petersen, Jens-Phillip

    The paper evaluates the current status of community energy planning in northern Europe via a review of literature, practice and the performance of a barrier analysis for successful community energy planning. Main findings of the paper are that current community energy planning lacks a systematic...... 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...... (CEP), is presented. The methodology was applied in a case study in Germany. With CEPs, a possibility to merge qualitative data from local settings into generic energy modelling is shown, which could contribute to improved community energy strategies....

  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. 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

  17. 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...

  18. Multi-step simultaneous changes Constructive Heuristic Algorithm for Transmission Network Expansion Planning

    Energy Technology Data Exchange (ETDEWEB)

    Bustamante-Cedeno, Enrique; Arora, Sant [Industrial and Systems Engineering Division, Mechanical Engineering Department, University of Minnesota, 111 Church Street, S.E., Minneapolis, MN 55455 (United States)

    2009-04-15

    In this paper, a Constructive Heuristic Algorithm (CHA) is presented to solve the Transmission Network Expansion Planning Problem (TNEP), a complex non-convex Mixed Integer Non-Linear Programming (MINLP) problem with multiple local minima. In the proposed algorithm, the non-linearities are resolved through the following feature: when discrete decision variables are given, the model becomes linear in the continuous variables. A CHA is developed which improves the current solution by implementing multiple step simultaneous changes over a number of saturated transmission lines, in contrast to the approach traditionally followed, which implements one change at a time. Solutions to test problems are computed. (author)

  19. Design Optimization of Expansion Driven Components for the HJ-1-C Satellite

    Directory of Open Access Journals (Sweden)

    Huang Zhi-rong

    2014-06-01

    Full Text Available Expansion-driven HJ-1-C satellite components are prone to fatigue and fracture; thus, a reliability study on the optimal design is performed. According to the Failure Mode and Effects Analysis (FMEA of the components, the main failure modes are stress relaxation and impact breakage of the torsion and scroll springs. On the basis of the failure modes, a prototype spring is tested, and the relative reliabilities are calculated. Then, reliability measures are proposed, and the design optimization of the springs is carried out. The improvements introduced by the prototype spring are indicative of the effectiveness and reliability of the design optimization process, which can help design and analyze similar antenna reflectors in the future.

  20. 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...

  1. 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.

  2. Optimizing Rank of Landscape Planning Works of Urban Wetland Park

    Institute of Scientific and Technical Information of China (English)

    Qiao Li-fang; Zhang Yi-chuan; Qi An-guo; Li Xin-zheng

    2012-01-01

    Classifying and ranking the huge amounts of landscape planning works of urban wetland park is always difficult due to the multi-functions (ecological, leisure, educational and disaster prevention) of the urban wetland park. Therefore, an optimizing rank system is urgently needed. Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) models were used to rank the planning works of 30 urban wetland park based on four mainly factors, which included landscape ecological planning, landscape planning, ecological planning and economic planning. The study indicated that the AHP- TOPSIS model had good discrimination in the classification and ranking of landscape planning works of urban wetland park and it was also applicable to the planning works of other urban greenbelts.

  3. Brachytherapy optimal planning with application to intravascular radiation therapy

    DEFF Research Database (Denmark)

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

    1999-01-01

    . Dose rate calculations are based on the sosimetry formulation of the American Association of Physicists in Medicine, Task Group 43. We apply the technique to optimal planning for intravascular brachytherapy of intimal hyperplasia using ultrasound data and 192Ir seeds. The planning includes...

  4. The study of cuckoo optimization algorithm for production planning problem

    OpenAIRE

    Akbarzadeh, Afsane; Shadkam, Elham

    2015-01-01

    Constrained Nonlinear programming problems are hard problems, and one of the most widely used and common problems for production planning problem to optimize. In this study, one of the mathematical models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is efficient method to solve continues non linear problem. Moreover, mentioned models of production planning solved with Genetic algorithm and Lingo software and the results will compared. The Cucko...

  5. Optimizing nursing human resource planning in British Columbia.

    Science.gov (United States)

    Lavieri, Mariel S; Puterman, Martin L

    2009-06-01

    This paper describes a linear programming hierarchical planning model that determines the optimal number of nurses to train, promote to management and recruit over a 20 year planning horizon to achieve specified workforce levels. Age dynamics and attrition rates of the nursing workforce are key model components. The model was developed to help policy makers plan a sustainable nursing workforce for British Columbia, Canada. An easy to use interface and considerable flexibility makes it ideal for scenario and "What-If?" analyses.

  6. Optimizing Long-Term Capital Planning for Special Operations Forces

    Science.gov (United States)

    2015-06-01

    TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES by Gretchen M. Radke June 2015 Thesis Advisor: Emily Craparo Co-Advisor: Jonathan Alt...REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE OPTIMIZING LONG-TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES 5...words) The United States Special Operations Command (USSOCOM) J8 directorate is responsible for planning long-range capital expenditure for Special

  7. Reliability worth applied to transmission expansion planning based on ant colony system

    Energy Technology Data Exchange (ETDEWEB)

    Leite da Silva, Armando M.; Rezende, Leandro S. [Institute of Electric Systems and Energy, Federal University of Itajuba, UNIFEI (Brazil); da Fonseca Manso, Luiz A.; de Resende, Leonidas C. [Department of Electrical Engineering, Federal University of Sao Joao del Rei, UFSJ (Brazil)

    2010-12-15

    This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution, bearing in mind investment cost and reliability worth. Reliability worth is considered through the assessment of the interruption costs represented by the index LOLC - loss of load cost. The focus of this work is the development of a tool for the multi-stage planning of transmission systems and how reliability aspects can influence on the decision-making process. The applications of the proposed methodology are illustrated through case studies carried out using a test system and a real sub-transmission network. (author)

  8. 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.

  9. 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)

  10. A model for integrated analysis of generation capacity expansion and financial planning

    Energy Technology Data Exchange (ETDEWEB)

    Majumdar, S. [Indian Inst. of Management, Ahmedabad (India). Public Systems Group; Chattopadhyay, D. [Univ. of Canterbury, Christchurch (New Zealand). Dept. of Management

    1999-05-01

    This paper discusses the need for an integrated analysis of investment and financing decisions in the context of electricity generation capacity addition planning. The traditional mathematical programming model for investment planning and its potential enhancement to encompass financing decisions in a unified framework have been discussed. The integrated investment-finance model for power system is formulated. The model is implemented for a well-known investment planning case study and the various investment-financing interactions have been discussed. The results indicate that the interaction of financing and investment decisions could be very significant and needs to be accounted for capacity planning optimization exercises. This is particularly relevant for utilities in a competitive environment.

  11. 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

  12. 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)

  13. OPTIMIZED AGRICULTURAL PLANNING OF SUGARCANE USING LINEAR PROGRAMMING

    Directory of Open Access Journals (Sweden)

    Maximiliano Salles Scarpari* and Edgar Gomes Ferreira de Beauclair**

    2010-03-01

    Full Text Available Optimized agricultural planning is a fundamental activity in business profitability because it can increase the returns from an operation with low additional costs. Nonetheless, the use of operations research adapted to sugarcane plantation management is still limited, resulting in decision-making at management level being primarily empirical. The goal of this work was to develop an optimized planning model for sugarcane farming using a linear programming tool. The program language used was General Algebraic Modelling System (GAMS as this system was seen to be an excellent tool to allow profit maximization and harvesting time schedule optimization in the sugar mill studied. The results presented support this optimized planning model as being a very useful tool for sugarcane management.

  14. Optimal Planning of Maintenance of Concrete Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    1997-01-01

    of initiation of cerrosion in reinforced concrete structures as function of time. Further clifferent strategies for maintenance and repairs are formulated and it is shown how the probabilistic models can be used to estimate the expected costs for different strategies and how to select the optimal strategy....

  15. Modeling the effects of demand response on generation expansion planning in restructured power systems

    Institute of Scientific and Technical Information of China (English)

    Mahdi SAMADI; Mohammad Hossein JAVIDI; Mohammad Sadegh GHAZIZADEH

    2013-01-01

    Demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operation of power sys-tems by deployment demand response. The growth of customers’ participation in such programs may affect the planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. The effects of demand responsiveness are studied from the points of view of both customers and generation companies. The pro-posed model has been applied to a modified IEEE 30-bus system and the results of the study are discussed. Simulation results show that reducing just 3%of the customers’ demand (due to price elasticity) may result in a benefit of about 10%for customers in the long term.

  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. 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)

  18. Optimal Planning of Communication System of CPS for Distribution Network

    Directory of Open Access Journals (Sweden)

    Ting Yang

    2017-01-01

    Full Text Available IoT is the technical basis to realize the CPS (Cyber Physical System for distribution networks, with which the complex system becomes more intelligent and controllable. Because of the multihop and self-organization characteristics, the large-scale heterogeneous CPS network becomes more difficult to plan. Using topological potential theory, one of typical big data analysis technologies, this paper proposed a novel optimal CPS planning model. Topological potential equalization is considered as the optimization objective function in heterogeneous CPS network with the constraints of communication requirements, physical infrastructures, and network reliability. An improved binary particle swarm optimization algorithm is proposed to solve this complex optimal problem. Two IEEE classic examples are adopted in the simulation, and the results show that, compared with benchmark algorithms, our proposed method can provide an effective topology optimization scheme to improve the network reliability and transmitting performance.

  19. 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.

  20. 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.

  1. Optimal Planning of Maintenance of Concrete Structures

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Engelund, S.

    1997-01-01

    Chloride ingress and progress of the carbonation front into concrete are considered. Probabilistic models are formulated and it is shown how the parameters in the models can be estimated on the basis of measurements using Bayesian statistics. The stochastic model is used to estimate the probability...... of initiation of cerrosion in reinforced concrete structures as function of time. Further clifferent strategies for maintenance and repairs are formulated and it is shown how the probabilistic models can be used to estimate the expected costs for different strategies and how to select the optimal strategy....

  2. 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.

  3. Optimal partial-arcs in VMAT treatment planning

    CERN Document Server

    Wala, Jeremiah; Chen, Wei; Craft, David

    2012-01-01

    Purpose: To improve the delivery efficiency of VMAT by extending the recently published VMAT treatment planning algorithm vmerge to automatically generate optimal partial-arc plans. Methods and materials: 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. Results: Partial-arc plans are created using pmerge for a lung, liver and prostate case, with final treatment times of 127, 245 and 147 seconds. Treatment times...

  4. Optimal quality reporting in markets for health plans.

    Science.gov (United States)

    Glazer, Jacob; McGuire, Thomas G

    2006-03-01

    Quality reports about health plans and providers are becoming more prevalent in health care markets. This paper casts the decision about what information to report to consumers about health plans as a policy decision. In a market with adverse selection, complete information about quality leads to inefficient outcomes. In a Rothschild-Stiglitz model, we show that averaging quality information into a summary report can enforce pooling in health insurance, and by choice of the right weights in the averaged report, a payer or regulator can induce first-best quality choices. The optimal quality report is as powerful as optimal risk adjustment in correcting adverse selection inefficiencies.

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

    Energy Technology Data Exchange (ETDEWEB)

    Shayanfar, H.A.; Lahiji, A. Saliminia; Aghaei, J.; Rabiee, A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology (IUST), Tehran (Iran)

    2009-05-15

    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)

  6. A Novel Method for Calculating Demand Not Served for Transmission Expansion Planning

    CERN Document Server

    Gupta, Neeraj; Kalra, Prem Kumar

    2011-01-01

    Restructuring of the power market introduced demand uncertainty in transmission expansion planning (TEP), which in turn also requires an accurate estimation of demand not served (DNS). Unfortunately, the graph theory based minimum-cut maximum-flow (MCMF) approach does not ensure that electrical laws are followed. Nor can it be used for calculating DNS at individual buses. In this letter, we propose a generalized load flow based methodology for calculating DNS. This procedure is able to calculate simultaneously generation not served (GNS) and wheeling loss (WL). Importantly, the procedure is able to incorporate the effect of I2R losses, excluded in MCMF approach. Case study on a 5-bus IEEE system shows the effectiveness of the proposed approach over existing method.

  7. Practice-Oriented Optimization of Distribution Network Planning Using Metaheuristic Algorithms

    NARCIS (Netherlands)

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

    2014-01-01

    Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, many optimization approac

  8. 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

  9. Optimal trajectory planning for natural biped walking locomotion

    Institute of Scientific and Technical Information of China (English)

    刘荣强; 焦映厚; 陈照波

    2003-01-01

    An optimal trajectory planning method has been proposed for the walking locomotion of a biped me-c hanical system with thighs, shanks and small feet, which is modelled as a 3-DOF link system consisting of aninverted pendulum and a 2-DOF swing leg. The locomotion of swing and supporting legs is solved by the optimaltrajectory planning based on function approximation. The optimal trajectory planning based on function approxi-mation. The optimal walking locomotion solution with minimum square of input torque exhibits a natural walkinggait with one step period of 0.64 s similar to the human walking gait by using the link parameters of an adult'sleg. It is concluded from the computation results that the method proposed in this paper has been proved to bean effective tool for solving the optimal walking locomotion and joint control torque problems for a 3-DOF bipedmechanism; when the ankle joint of the supporting leg is a passive joint, a nearly, optimal walking solution canbe obtained at t1 = 0. 49 s and t2 = 10 s, and however, when the knee is a passive joint, it is impossible to ob-tain a solution which satisfies the constraint condition; for the link parameters used in this paper, the length ofan optimal stride is 0.3 m.

  10. Determining Optimal Link Capacity Expansions in Road Networks Using Cuckoo Search Algorithm with Lévy Flights

    Directory of Open Access Journals (Sweden)

    Ozgur Baskan

    2013-01-01

    Full Text Available During the last two decades, Continuous Network Design Problem (CNDP has received much more attention because of increasing trend of traffic congestion in road networks. In the CNDP, the problem is to find optimal link capacity expansions by minimizing the sum of total travel time and investment cost of capacity expansions in a road network. Considering both increasing traffic congestion and limited budgets of local authorities, the CNDP deserves to receive more attention in order to use available budget economically and to mitigate traffic congestion. The CNDP can generally be formulated as bilevel programming model in which the upper level deals with finding optimal link capacity expansions, whereas at the lower level, User Equilibrium (UE link flows are determined by Wardrop’s first principle. In this paper, cuckoo search (CS algorithm with Lévy flights is introduced for finding optimal link capacity expansions because of its recent successful applications in solving such complex problems. CS is applied to the 16-link and Sioux Falls networks and compared with available methods in the literature. Results show the potential of CS for finding optimal or near optimal link capacity expansions in a given road network.

  11. Synthesis and assessment of pareto-optimal grid-expansion measures; Erzeugung und Bewertung pareto-optimaler Netz-Ausbauoptionen

    Energy Technology Data Exchange (ETDEWEB)

    Scheufen, Martin; Natemeyer, Hendrik; Surmann, Yvonne; Schnettler, Armin [RWTH Aachen Univ. (Germany). Inst. fuer Hochspannungstechnik

    2012-07-01

    This paper presents a methodology that generates transmission grid expansion options which are assessed under competing interests of technical, economic and ecological criteria. The results presented are based on a multi-objective evolutionary optimization approach (genetic algorithm, NSGA-II) in which each individual of the population is representing a grid expansion pattern. As network expansion option power flow controlling elements, such as FACTS and PSTs are considered in addition to line-additions. The results are demonstrated on a modified standard grid-model. The comparative assessment of the specific expansion options uses a modified optimal power flow method taking into account characteristically spatio-temporal correlated supply and load pattern. (orig.)

  12. Optimal vehicle planning and the search tour problem

    Science.gov (United States)

    Wettergren, Thomas A.; Bays, Matthew J.

    2016-05-01

    We describe a problem of optimal planning for unmanned vehicles and illustrate two distinct procedures for its solution. The problem under consideration, which we refer to as the search tour problem, involves the determination of multi-stage plans for unmanned vehicles conducting search operations. These types of problems are important in situations where the searcher has varying performance in different regions throughout the domain due to environmental complexity. The ability to provide robust planning for unmanned systems under difficult environmental conditions is critical for their use in search operations. The problem we consider consists of searches with variable times for each of the stages, as well as an additional degree of freedom for each stage to select from one of a finite set of operational configurations. As each combination of configuration and stage time leads to a different performance level, there is a need to determine the optimal configuration of these stages. When the complexity of constraints on total time, as well as resources expended at each stage for a given configuration, are added, the problem becomes one of non-trivial search effort allocation and numerical methods of optimization are required. We show two solution approaches for this numerical optimization problem. The first solution technique is to use a mixed-integer linear programming formulation, for which commercially available solvers can find optimal solutions in a reasonable amount of time. We use this solution as a baseline and compare against a new inner/outer optimization formulation. This inner/outer optimization compares favorably to the baseline solution, but is also amenable to adaptation as the search operation progresses. Numerical examples illustrate the utility of the approach for unmanned vehicle search planning.

  13. Explicit and convex optimization of plan quality measures in intensity-modulated radiation therapy treatment planning

    CERN Document Server

    Engberg, Lovisa; Forsgren, Anders; Hårdemark, Björn

    2016-01-01

    Given the widespread agreement that doses-at-volume play important roles in quality assessment of radiation therapy treatment plans, planning objectives that correlate well with explicit dose-at-volume optimization are likely to correlate well with plan quality. In this study, planning objectives are formulated to explicitly either minimize or maximize convex approximations of dose-at-volume, namely, mean-tail-doses. This is in contrast to the conventionally used planning objectives, which are used to maximize clinical goal fulfilment by relating to deviations from dose-at-volume thresholds. Advantages of the proposed planning objectives are investigated through juxtaposition with conventional objectives in a computational study of two patient cases, each with three doses-at-volume to be minimized subject to PTV coverage. With proposed planning objectives, this is translated into minimizing three mean-tail-doses. Comparison with conventional objectives is carried out in the dose-at-volume domain and in the no...

  14. Jar Decoding: Non-Asymptotic Converse Coding Theorems, Taylor-Type Expansion, and Optimality

    CERN Document Server

    Yang, En-Hui

    2012-01-01

    Recently, a new decoding rule called jar decoding was proposed; under jar decoding, a non-asymptotic achievable tradeoff between the coding rate and word error probability was also established for any discrete input memoryless channel with discrete or continuous output (DIMC). Along the path of non-asymptotic analysis, in this paper, it is further shown that jar decoding is actually optimal up to the second order coding performance by establishing new non-asymptotic converse coding theorems, and determining the Taylor expansion of the (best) coding rate $R_n (\\epsilon)$ of finite block length for any block length $n$ and word error probability $\\epsilon$ up to the second order. Finally, based on the Taylor-type expansion and the new converses, two approximation formulas for $R_n (\\epsilon)$ (dubbed "SO" and "NEP") are provided; they are further evaluated and compared against some of the best bounds known so far, as well as the normal approximation of $R_n (\\epsilon)$ revisited recently in the literature. It t...

  15. 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

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

    Science.gov (United States)

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

    2012-08-01

    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. 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. 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. The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

  17. Model-based Optimal Evacuation Planning anticipating Traveler Compliance Behavior

    NARCIS (Netherlands)

    Pel, A.J.; Huibregtse, O.L.; Hoogendoorn, S.P.; Bliemer, M.C.J.

    2010-01-01

    Instructing evacuees on their departure time, destination, and route can lead to more efficient evacuation traffic operations. While current evacuation plan optimization techniques are limited to assessing mandatory evacuation where travelers strictly follow the instructions, in reality a share of t

  18. Resampling: an optimization method for inverse planning in robotic radiosurgery.

    Science.gov (United States)

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

    2006-11-01

    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.

  19. 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.

  20. Planning and Optimization Methods for Active Distribution Systems

    DEFF Research Database (Denmark)

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

    ”. This report assesses the various requirements to facilitate the transition towards active distribution systems (ADSs). Specifically, the report starts from a survey of requirements of planning methodologies and identifies a new framework and methodologies for short, medium and long term models for active...... in the distribution business since the exploitation of existing assets with Advanced Automation and Control may be a valuable alternative to network expansion or reinforcement. Information and communication technology (ICT) cannot be considered as a simple add-on of the power system and simultaneous analysis (co...

  1. Operations planning for agricultural harvesters using ant colony optimization

    Directory of Open Access Journals (Sweden)

    A. Bakhtiari

    2013-07-01

    Full Text Available An approach based on ant colony optimization for the generation for optimal field coverage plans for the harvesting operations using the optimal track sequence principle B-patterns was presented. The case where the harvester unloads to a stationary facility located out of the field area, or in the field boundary, was examined. In this operation type there are capacity constraints to the load that a primary unit, or a harvester in this specific case, can carry and consequently, it is not able to complete the task of harvesting a field area and therefore it has to leave the field area, to unload, and return to continue the task one or more times. Results from comparing the optimal plans with conventional plans generated by operators show reductions in the in-field nonworking distance in the range of 19.3-42.1% while the savings in the total non-working distance were in the range of 18-43.8%. These savings provide a high potential for the implementation of the ant colony optimization approach for the case of harvesting operations that are not supported by transport carts for the out-of-the-field removal of the crops, a practice case that is normally followed in developing countries, due to lack of resources.

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

    Energy Technology Data Exchange (ETDEWEB)

    Becker, Nir, E-mail: nbecker@telhai.ac.i [Department of Economics and Management, Tel-Hai College (Israel); Soloveitchik, David, E-mail: david_soloveitchik@yahoo.co [Energy and Economic Models, Jerusalem (Israel); Olshansky, Moshe, E-mail: olshansky@wehi.edu.a [Walter and Eliza Hall Institute, Melbourne (Australia)

    2011-07-15

    Highlights: {yields} Long term energy-environmental planning problems for the electricity sector. {yields} Environmental considerations in the capacity expansion plan. {yields} Modified version of WASP-IV as a multiple objective programming model. {yields} 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.

  3. Multiple Space Debris Collecting Mission -- Optimal Mission Planning

    CERN Document Server

    Cerf, Max

    2014-01-01

    This paper addresses the problem of planning successive Space Debris Collecting missions so that they can be achieved at minimal cost by a generic vehicle. The problem mixes combinatorial optimization to select and order the debris among a list of candidates, and continuous optimization to fix the rendezvous dates and to define the minimum fuel orbital maneuvers. The solution method proposed consists in three stages. Firstly the orbital transfer problem is simplified by considering a generic transfer strategy suited either to a high thrust or a low thrust vehicle. A response surface modelling is built by solving the reduced problem for all pairs of debris and for discretized dates, and storing the results in cost matrices. Secondly a simulated annealing algorithm is applied to find the optimal mission planning. The cost function is assessed by interpolation on the response surface based on the cost matrices. This allows the convergence of the simulated algorithm in a limited computation time, yielding an opti...

  4. GPU-based ultra fast IMRT plan optimization

    CERN Document Server

    Men, Chunhua; Choi, Dongju; Majumdar, Amitava; Zheng, Ziyi; Mueller, Klaus; Jiang, Steve B

    2009-01-01

    The widespread adoption of on-board volumetric imaging in cancer radiotherapy has stimulated research efforts to develop online adaptive radiotherapy techniques to handle the inter-fraction variation of the patient's geometry. Such efforts face major technical challenges to perform treatment planning in real-time. To overcome this challenge, we are developing a supercomputing online re-planning environment (SCORE) at the University of California San Diego (UCSD). As part of the SCORE project, this paper presents our work on the implementation of an intensity modulated radiation therapy (IMRT) optimization algorithm on graphics processing units (GPUs). We adopt a penalty-based quadratic optimization model, which is solved by using a gradient projection method with Armijo's line search rule. Our optimization algorithm has been implemented in CUDA for parallel GPU computing as well as in C for serial CPU computing for comparison purpose. A prostate IMRT case with various beamlet and voxel sizes was used to evalu...

  5. TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

    Science.gov (United States)

    Bergh, Christopher P.; Krzeczowski, Kenneth J.; Davis, Thomas J.; Denery, Dallas G. (Technical Monitor)

    1995-01-01

    A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

  6. Spatial Coverage Planning and Optimization for Planetary Exploration

    Science.gov (United States)

    Gaines, Daniel M.; Estlin, Tara; Chouinard, Caroline

    2008-01-01

    We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

  7. 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.

  8. ACO Algorithm Applied to Multi-Objectives Optimization of Capacity Expansion in Next Generation Wireless Network

    Directory of Open Access Journals (Sweden)

    Dac-Nhuong Le

    2013-09-01

    Full Text Available The optimal capacity expansion of base station subsystems in Next Generation Wireless Network (NGWN problem with respect to multi-demand type and system capacity constraints is known to be NP-complete. In this paper, we propose a novel ant colony optimization algorithm to solve a network topology has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. There are two important aspects of upgrading to NGWN. The first importance of backward compatibility with pre-existing networks, and the second is the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. Our objective function is the sources to concentrators connectivity costas well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We evaluate the performance of our algorithm with a set of real world and data randomly generated. Numerical results show that our algorithms is a promising approach to solve this problem.

  9. Using "big data" to optimally model hydrology and water quality across expansive regions

    Science.gov (United States)

    Roehl, E.A.; Cook, J.B.; Conrads, P.A.

    2009-01-01

    This paper describes a new divide and conquer approach that leverages big environmental data, utilizing all available categorical and time-series data without subjectivity, to empirically model hydrologic and water-quality behaviors across expansive regions. The approach decomposes large, intractable problems into smaller ones that are optimally solved; decomposes complex signals into behavioral components that are easier to model with "sub- models"; and employs a sequence of numerically optimizing algorithms that include time-series clustering, nonlinear, multivariate sensitivity analysis and predictive modeling using multi-layer perceptron artificial neural networks, and classification for selecting the best sub-models to make predictions at new sites. This approach has many advantages over traditional modeling approaches, including being faster and less expensive, more comprehensive in its use of available data, and more accurate in representing a system's physical processes. This paper describes the application of the approach to model groundwater levels in Florida, stream temperatures across Western Oregon and Wisconsin, and water depths in the Florida Everglades. ?? 2009 ASCE.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Qianqian; Blohm, Andrew J.; 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.

  11. Speed optimized influence matrix processing in inverse treatment planning tools

    Energy Technology Data Exchange (ETDEWEB)

    Ziegenhein, Peter; Wilkens, Jan J; Nill, Simeon; Oelfke, Uwe [German Cancer Research Center (DKFZ), Department of Medical Physics in Radiation Oncology, Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Ludwig, Thomas [University of Heidelberg, Institute of Computer Science, Research Group Parallel and Distributed Systems, Im Neuenheimer Feld 348, 69120 Heidelberg (Germany)], E-mail: p.ziegenhein@dkfz.de, E-mail: u.oelfke@dkfz.de

    2008-05-07

    An optimal plan in modern treatment planning tools is found through the use of an iterative optimization algorithm, which deals with a high amount of patient-related data and number of treatment parameters to be optimized. Thus, calculating a good plan is a very time-consuming process which limits the application for patients in clinics and for research activities aiming for more accuracy. A common technique to handle the vast amount of radiation dose data is the concept of the influence matrix (DIJ), which stores the dose contribution of each bixel to the patient in the main memory of the computer. This study revealed that a bottleneck for the optimization time arises from the data transfer of the dose data between the memory and the CPU. In this note, we introduce a new method which speeds up the data transportation from stored dose data to the CPU. As an example we used the DIJ approach as is implemented in our treatment planning tool KonRad, developed at the German Cancer Research Center (DKFZ) in Heidelberg. A data cycle reordering method is proposed to take the advantage of modern memory hardware. This induces a minimal eviction policy which results in a memory behaviour exhibiting a 2.6 times faster algorithm compared to the naive implementation. Although our method is described for the DIJ approach implemented in KonRad, we believe that any other planning tool which uses a similar approach to store the dose data will also benefit from the described methods. (note)

  12. Optimality of Profit-Including Prices Under Ideal Planning

    Science.gov (United States)

    Samuelson, Paul A.

    1973-01-01

    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. PMID:16592102

  13. Novel tools for stepping source brachytherapy treatment planning: Enhanced geometrical optimization and interactive inverse planning

    Energy Technology Data Exchange (ETDEWEB)

    Dinkla, Anna M., E-mail: a.m.dinkla@amc.uva.nl; Laarse, Rob van der; Koedooder, Kees; Petra Kok, H.; Wieringen, Niek van; Pieters, Bradley R.; Bel, Arjan [Department of Radiation Oncology, Academic Medical Center Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ (Netherlands)

    2015-01-15

    Purpose: Dose optimization for stepping source brachytherapy can nowadays be performed using automated inverse algorithms. Although much quicker than graphical optimization, an experienced treatment planner is required for both methods. With automated inverse algorithms, the procedure to achieve the desired dose distribution is often based on trial-and-error. Methods: A new approach for stepping source prostate brachytherapy treatment planning was developed as a quick and user-friendly alternative. This approach consists of the combined use of two novel tools: Enhanced geometrical optimization (EGO) and interactive inverse planning (IIP). EGO is an extended version of the common geometrical optimization method and is applied to create a dose distribution as homogeneous as possible. With the second tool, IIP, this dose distribution is tailored to a specific patient anatomy by interactively changing the highest and lowest dose on the contours. Results: The combined use of EGO–IIP was evaluated on 24 prostate cancer patients, by having an inexperienced user create treatment plans, compliant to clinical dose objectives. This user was able to create dose plans of 24 patients in an average time of 4.4 min/patient. An experienced treatment planner without extensive training in EGO–IIP also created 24 plans. The resulting dose-volume histogram parameters were comparable to the clinical plans and showed high conformance to clinical standards. Conclusions: Even for an inexperienced user, treatment planning with EGO–IIP for stepping source prostate brachytherapy is feasible as an alternative to current optimization algorithms, offering speed, simplicity for the user, and local control of the dose levels.

  14. Optimizing global liver function in radiation therapy treatment planning

    Science.gov (United States)

    Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

    2016-09-01

    Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and

  15. Optimizing global liver function in radiation therapy treatment planning

    Science.gov (United States)

    Wu, Victor W; Epelman, Marina A; Wang, Hesheng; Romeijn, H Edwin; Feng, Mary; Cao, Yue; Haken, Randall K Ten; Matuszak, Martha M

    2017-01-01

    Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (ℓEUD) (conventional ‘ℓEUD model’), the so-called perfusion-weighted ℓEUD (fEUD) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting ℓEUD, fEUD, and GLF plans delivering the same target ℓEUD are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6%(7.5%) more liver function than the fEUD (ℓEUD) plan does in 2D cases, and up to 4.5%(5.6%) in 3D cases. The GLF and fEUD plans worsen in ℓEUD of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than ℓEUD model optimization does, the GLF model directly optimizes a more clinically

  16. 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* (TGRRT* 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.

  17. 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.

  18. Optimal Path Planning for Mobile Robot Using Tailored Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Dong Xiao Xian

    2013-07-01

    Full Text Available During routine inspecting, mobile robot may be requested to visit multiple locations to execute special tasks occasionally. This study aims at optimal path planning for multiple goals visiting task based on tailored genetic algorithm. The proposed algorithm will generate an optimal path that has the least idle time, which is proven to be more effective on evaluating a path in our previous work. In proposed algorithm, customized chromosome representing a path and genetic operators including repair and cut are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.

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

    DEFF Research Database (Denmark)

    Konicz, Agnieszka Karolina; Mulvey, John M.

    2015-01-01

    The paper provides some guidelines to individuals with defined contribution (DC) pension plans on how to manage pension savings both before and after retirement. We argue that decisions regarding investment, annuity payments, and the size of death sum should not only depend on the individual’s age...... 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...

  20. 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.

  1. The optimization of operating parameters on microalgae upscaling process planning.

    Science.gov (United States)

    Ma, Yu-An; Huang, Hsin-Fu; Yu, Chung-Chyi

    2016-03-01

    The upscaling process planning developed in this study primarily involved optimizing operating parameters, i.e., dilution ratios, during process designs. Minimal variable cost was used as an indicator for selecting the optimal combination of dilution ratios. The upper and lower mean confidence intervals obtained from the actual cultured cell density data were used as the final cell density stability indicator after the operating parameters or dilution ratios were selected. The process planning method and results were demonstrated through three case studies of batch culture simulation. They are (1) final objective cell densities were adjusted, (2) high and low light intensities were used for intermediate-scale cultures, and (3) the number of culture days was expressed as integers for the intermediate-scale culture.

  2. 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.

  3. Resource-Optimal Planning For An Autonomous Planetary Vehicle

    Directory of Open Access Journals (Sweden)

    Giuseppe Della Penna

    2010-07-01

    Full Text Available Autonomous planetary vehicles, also known as rovers, are small autonomous vehicles equipped with a variety of sensors used to perform exploration and experiments on a planet’s surface. Rovers work in a partially unknown environment, with narrow energy/time/movement constraints and, typically, small computational resources that limit the complexity of on-line planning and scheduling, thus they represent a great challenge in the field of autonomous vehicles. Indeed, formal models for such vehicles usually involve hybrid systems with nonlinear dynamics, which are difficult to handle by most of the current planning algorithms and tools. Therefore, when offline planning of the vehicle activities is required, for example for rovers that operate without a continuous Earth supervision, such planning is often performed on simplified models that are not completely realistic. In this paper we show how the UPMurphi model checking based planning tool can be used to generate resource-optimal plans to control the engine of an autonomous planetary vehicle, working directly on its hybrid model and taking into account several safety constraints, thus achieving very accurate results.

  4. Optimal passive optical network planning under demand uncertainty

    OpenAIRE

    2014-01-01

    As a result of ever-increasing demand for access level bandwidth, long deployment cycles and the popularisation of more economically viable Point-to-Multipoint (P2MP) networks, service providers are moving to extensively future-proof fibre technologies to connect consumers. Of these, the Passive Optical Network (PON) is the most prevalent. Though the optimal planning of these networks have been studied by a number of authors recently, the typical situation where consumer ...

  5. Ant colony optimized planning for unmanned surface marine vehicles

    OpenAIRE

    Benítez, J.M.; Jiménez, Juan F.; Jose M. Girón-Sierra

    2010-01-01

    This paper presents some results achieved from a preliminary study on the use of the Ant Colony Algorithm to plan feasible optimal or suboptimal trajectories for an autonomous ship manoeuvring. The scenario, for this preliminary work, comprises only open sea manoeuvres. The goal involves obtaining the least time consuming ship trajectory between to points, departing from the start point with arbitrary initial speed and attitude values and arriving to the end point with prede...

  6. Path Planning Optimization for Teaching and Playback Welding Robot

    Directory of Open Access Journals (Sweden)

    Yuehai Wang

    2013-02-01

    Full Text Available Path planning for the industrial robot plays an important role in the intelligent control of robot. Tradition strategies, including model-based methods and human taught based methods, find it is difficult to control manipulator intelligently and optically. Thus, it is hard to ensure the better performance and lower energy consumption even if the same welding task was executed repeatedly. A path planning optimization method was proposed to add learning ability to teaching and playback welding robot. The optimization was divided into the welding points sequence improvement and trajectory improvement, which was done both on-line and off-line. Points sequence optimization was modeled as TSP and was continuously improved by genetic algorithm based strategy, while the trajectory between two welding points was on-line improved by an try-and-error strategy where the robot try different trajectory from time to time so as to search a better plan. Simulation results verified that this control strategy reduced the time and energy cost as compared with the man-made fix-order sequence. Our method prevents the robot from the computation-intensive model-based control, and offers a convenient way for self-improvement on the basis of human teaching.

  7. 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.

  8. 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.

  9. A stochastic optimization approach for integrated urban water resource planning.

    Science.gov (United States)

    Huang, Y; Chen, J; Zeng, S; Sun, F; Dong, X

    2013-01-01

    Urban water is facing the challenges of both scarcity and water quality deterioration. Consideration of nonconventional water resources has increasingly become essential over the last decade in urban water resource planning. In addition, rapid urbanization and economic development has led to an increasing uncertain water demand and fragile water infrastructures. Planning of urban water resources is thus in need of not only an integrated consideration of both conventional and nonconventional urban water resources including reclaimed wastewater and harvested rainwater, but also the ability to design under gross future uncertainties for better reliability. This paper developed an integrated nonlinear stochastic optimization model for urban water resource evaluation and planning in order to optimize urban water flows. It accounted for not only water quantity but also water quality from different sources and for different uses with different costs. The model successfully applied to a case study in Beijing, which is facing a significant water shortage. The results reveal how various urban water resources could be cost-effectively allocated by different planning alternatives and how their reliabilities would change.

  10. Study of Multi-objective Fuzzy Optimization for Path Planning

    Institute of Scientific and Technical Information of China (English)

    WANG Yanyang; WEI Tietao; QU Xiangju

    2012-01-01

    During path planning,it is necessary to satisfy the requirements of multiple objectives.Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker.The decision-maker,however,has illegibility for understanding the requirements of multiple objectives and the subjectivity inclination.It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning.Based on Voronoi diagram method for the path planning,this paper studies the synthesis method of the multi-objective cost performance index.According to the application of the cost performance index to the path planning based on Voronoi diagram method,this paper analyzes the cost performance index which has been referred to at present.The analysis shows the insufficiency of the cost performance index at present,i.e.,it is difficult to synthesize sub-objective functions because of the great disparity of the sub-objective functions.Thus,a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy,and an improved performance index is established,which could coordinate the weight conflict of the sub-objective functions.Finally,the experimental result shows the effectiveness of the proposed approach.

  11. 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.

  12. Wind farm operation planning using optimal pitch angle pattern (OPAP)

    Energy Technology Data Exchange (ETDEWEB)

    Moskalenko, Natalia S.; Rudion, K. [Magdeburg Univ. (Germany). Chair for Electric Power Networks and Renewable Energy Sources

    2011-07-01

    This paper presents the possibilities of optimal operation planning to maximize the energy production from a wind farm based on optimal pitch angle pattern (OPAP). The current status of this work is to investigate the influence of the pitch angle adaptation of single wind turbines (WTs) on the overall energy yield of the farm. The approach proposed in this paper assumes a selective change of the pitch angle of the chosen WTs from the optimal value, which corresponds to the maximal utilization of kinetic energy from the wind flow, in order to minimize wake effect influence on the overall energy yield of the farm. In this paper the fundamental assumptions of the proposed approach will be specified and the calculation algorithm will be presented. Furthermore, an exemplary test system will be defined and chosen scenarios will be calculated in order to show the potentials of the OPAP method. (orig.)

  13. 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

  14. A novel adaptive Cuckoo search for optimal query plan generation.

    Science.gov (United States)

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  15. A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

    Directory of Open Access Journals (Sweden)

    Ramalingam Gomathi

    2014-01-01

    Full Text Available The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C standard for storing semantic web data is the resource description framework (RDF. To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  16. 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.

  17. 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...

  18. 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.

  19. Resource-Optimal Planning For An Autonomous Planetary Vehicle

    Directory of Open Access Journals (Sweden)

    Giuseppe Della Penna

    2010-07-01

    Full Text Available Autonomous planetary vehicles, also known as rovers, are small autonomous vehicles equipped with avariety of sensors used to perform exploration and experiments on a planet’s surface. Rovers work in apartially unknown environment, with narrow energy/time/movement constraints and, typically, smallcomputational resources that limit the complexity of on-line planning and scheduling, thus they representa great challenge in the field of autonomous vehicles. Indeed, formal models for such vehicles usuallyinvolve hybrid systems with nonlinear dynamics, which are difficult to handle by most of the currentplanning algorithms and tools. Therefore, when offline planning of the vehicle activities is required, forexample for rovers that operate without a continuous Earth supervision, such planning is often performedon simplified models that are not completely realistic. In this paper we show how the UPMurphi modelchecking based planning tool can be used to generate resource-optimal plans to control the engine of anautonomous planetary vehicle, working directly on its hybrid model and taking into account severalsafety constraints, thus achieving very accurate results.

  20. Robust, Optimal Water Infrastructure Planning Under Deep Uncertainty Using Metamodels

    Science.gov (United States)

    Maier, H. R.; Beh, E. H. Y.; Zheng, F.; Dandy, G. C.; Kapelan, Z.

    2015-12-01

    Optimal long-term planning plays an important role in many water infrastructure problems. However, this task is complicated by deep uncertainty about future conditions, such as the impact of population dynamics and climate change. One way to deal with this uncertainty is by means of robustness, which aims to ensure that water infrastructure performs adequately under a range of plausible future conditions. However, as robustness calculations require computationally expensive system models to be run for a large number of scenarios, it is generally computationally intractable to include robustness as an objective in the development of optimal long-term infrastructure plans. In order to overcome this shortcoming, an approach is developed that uses metamodels instead of computationally expensive simulation models in robustness calculations. The approach is demonstrated for the optimal sequencing of water supply augmentation options for the southern portion of the water supply for Adelaide, South Australia. A 100-year planning horizon is subdivided into ten equal decision stages for the purpose of sequencing various water supply augmentation options, including desalination, stormwater harvesting and household rainwater tanks. The objectives include the minimization of average present value of supply augmentation costs, the minimization of average present value of greenhouse gas emissions and the maximization of supply robustness. The uncertain variables are rainfall, per capita water consumption and population. Decision variables are the implementation stages of the different water supply augmentation options. Artificial neural networks are used as metamodels to enable all objectives to be calculated in a computationally efficient manner at each of the decision stages. The results illustrate the importance of identifying optimal staged solutions to ensure robustness and sustainability of water supply into an uncertain long-term future.

  1. Model-based optimization of perlite expansion via a Response Surface Method (RSM)

    OpenAIRE

    2013-01-01

    Conventional perlite expansion suffers certain well-known shortcomings compromising its viability and the adherence of expanded perlite to modern technical specifications for high-quality insulation materials. A new perlite expansion process has been designed and a vertical electrical furnace for perlite expansion has been constructed to overcome such drawbacks, with concurrent modeling studies (Angelopoulos et al., 2013 [1]). Having already accomplished the production of various expanded per...

  2. Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

    Directory of Open Access Journals (Sweden)

    Antonio H. Escobar Z.

    2011-01-01

    Full Text Available  This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations. 

  3. 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.

  4. Optimal Path Planning for Minimizing Base Disturbance of Space Robot

    Directory of Open Access Journals (Sweden)

    Xiao-Peng Wei

    2016-03-01

    Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.

  5. Optimal Path Planning for Minimizing Base Disturbance of Space Robot

    Directory of Open Access Journals (Sweden)

    Xiao-Peng Wei

    2016-03-01

    Full Text Available The path planning of free-floating space robot in space on-orbit service has been paid more and more attention. The problem is more complicated because of the interaction between the space robot and base. Therefore, it is necessary to minimize the base position and attitude disturbance to improve the path planning of free-floating space robot, reducing the fuel consumption for the position and attitude maintenance. In this paper, a reasonable path planning method to solve the problem is presented, which is feasible and relatively simple. First, the kinematic model of 6 degrees of freedom free-floating space robot is established. And then the joint angles are parameterized using the 7th order polynomial sine functions. The fitness function is defined according to the position and attitude of minimizing base disturbance and constraints of space robot. Furthermore, an improved chaotic particle swarm optimization (ICPSO is presented. The proposed algorithm is compared with the standard PSO and CPSO algorithm in the literature by the experimental simulation. The simulation results demonstrate that the proposed algorithm is more effective than the two other approaches, such as easy to find the optimal solution, and this method could provide a satisfactory path for the free-floating space robot.

  6. A treatment planning code for inverse planning and 3D optimization in hadrontherapy.

    Science.gov (United States)

    Bourhaleb, F; Marchetto, F; Attili, A; Pittà, G; Cirio, R; Donetti, M; Giordanengo, S; Givehchi, N; Iliescu, S; Krengli, M; La Rosa, A; Massai, D; Pecka, A; Pardo, J; Peroni, C

    2008-09-01

    The therapeutic use of protons and ions, especially carbon ions, is a new technique and a challenge to conform the dose to the target due to the energy deposition characteristics of hadron beams. An appropriate treatment planning system (TPS) is strictly necessary to take full advantage. We developed a TPS software, ANCOD++, for the evaluation of the optimal conformal dose. ANCOD++ is an analytical code using the voxel-scan technique as an active method to deliver the dose to the patient, and provides treatment plans with both proton and carbon ion beams. The iterative algorithm, coded in C++ and running on Unix/Linux platform, allows the determination of the best fluences of the individual beams to obtain an optimal physical dose distribution, delivering a maximum dose to the target volume and a minimum dose to critical structures. The TPS is supported by Monte Carlo simulations with the package GEANT3 to provide the necessary physical lookup tables and verify the optimized treatment plans. Dose verifications done by means of full Monte Carlo simulations show an overall good agreement with the treatment planning calculations. We stress the fact that the purpose of this work is the verification of the physical dose and a next work will be dedicated to the radiobiological evaluation of the equivalent biological dose.

  7. Optimal Motion Planning for Differentially Flat Underactuated Mechanical Systems

    Institute of Scientific and Technical Information of China (English)

    HE Guangping; GENG Zhiyong

    2009-01-01

    Underactuated mechanical system has less independent inputs than the degrees of freedom(DOF) of the mechanism. The energy efficiency of this class of mechanical systems is an essential problem in practice. On the basis of the sufficient and necessary condition that concludes a single input nonlinear system is differentially flat, it is shown that the flat output of the single input tmderactuated mechanical system can be obtained by finding a smooth output function such that the relative degree of the system equals to the dimension of the state space. If the fiat output of the underactuated system can be solved explicitly, and by constructing a smooth curve with satisfying given boundary conditions in flat output space, an energy efficiency optimization method is proposed for the motion planning of the differentially fiat underactuated mechanical systems. The inertia wheel pendulum is used to verify the proposed optimization method, and some numerical simulations show that the presented optimal motion planning method can efficaciously reduce the energy cost for given control tasks.

  8. Collaborative mission planning for UAV cluster to optimize relay distance

    Science.gov (United States)

    Tanil, Cagatay; Warty, Chirag; Obiedat, Esam

    Unmanned Aerial Vehicles (UAVs) coordinated path planning and intercommunication for visual exploration of a geographical region has recently become crucial. Multiple UAVs cover larger area than a single UAV and eliminate blind spots. To improve the surveillance, survivability and quality of the communication, we propose two algorithms for the route planning of UAV cluster operated in obstacle rich environment: (i) Multiple Population Genetic Algorithm (MPGA) (ii) Relay Selection Criteria (RSC). The main objective of MPGA is to minimize the total mission time while maintaining an optimal distance for communication between the neighboring nodes. MPGA utilizes evolutionary speciation techniques with a novel Feasible Population Creation Method (FPCM) and enhanced Inter-species Crossover Mechanism (ISCM) to obtain diversified routes in remarkably short time. In obtaining collision-free optimum paths, UAVs are subjected to constraints such as limited communication range, maximum maneuverability and fuel capacity. In addition to the path planning, RSC is developed for selection of UAVs relay nodes that is based on the location of the relay relative to source and destination. It is crucial since the Bit Error Rate (BER) performance of the link significantly depends on the location of the selected relay. In this paper, path planning and relay allocation algorithms are combined to have a seamless high quality monitoring of the region and to provide superior Quality of Service (QoS) for audio-video applications. Also, simulations in different operation zones with a cluster of up to six UAVs are performed to verify the feasibility of the proposed algorithms both in optimality and computation time.

  9. An Optimal Capacity Planning Model for General Cargo Seaport

    Directory of Open Access Journals (Sweden)

    Čedomir Dundović

    2012-10-01

    Full Text Available In this paper the application of the queuing the01y in optimalcapacity planning for general cargo seaport is presented.The seaport as a queuing syslem is defined and tlws, on the basisof the arrival and serviced number of ships in an obsen•edtime unit, the appropriate operating indicators of a port systemare calculated. Using the model of total port costs, the munberof berths and cranes on the berth can be determined wherebythe optimal port system functioning is achieved.

  10. Optimal compensation for temporal uncertainty in movement planning.

    Directory of Open Access Journals (Sweden)

    Todd E Hudson

    2008-07-01

    Full Text Available Motor control requires the generation of a precise temporal sequence of control signals sent to the skeletal musculature. We describe an experiment that, for good performance, requires human subjects to plan movements taking into account uncertainty in their movement duration and the increase in that uncertainty with increasing movement duration. We do this by rewarding movements performed within a specified time window, and penalizing slower movements in some conditions and faster movements in others. Our results indicate that subjects compensated for their natural duration-dependent temporal uncertainty as well as an overall increase in temporal uncertainty that was imposed experimentally. Their compensation for temporal uncertainty, both the natural duration-dependent and imposed overall components, was nearly optimal in the sense of maximizing expected gain in the task. The motor system is able to model its temporal uncertainty and compensate for that uncertainty so as to optimize the consequences of movement.

  11. 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...

  12. 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.

  13. 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

    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......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...... be obtained in the blade root and tip sections. It is expected that this will lead to small changes in optimum blade designs. In this work, has been implemented, and the spanwise load distribution has been optimized to find the highest possible power production. For comparison, optimizations have been carried...

  14. Socio-economic and ecological impacts of global protected area expansion plans

    OpenAIRE

    Visconti, Piero; Bakkenes, Michel; Smith?, Robert J.; Joppa, Lucas; Sykes, Rachel E.

    2015-01-01

    Several global strategies for protected area (PA) expansion have been proposed to achieve the Convention on Biological Diversity's Aichi target 11 as a means to stem biodiversity loss, as required by the Aichi target 12. However, habitat loss outside PAs will continue to affect habitats and species, and PAs may displace human activities into areas that might be even more important for species persistence. Here we measure the expected contribution of PA expansion strategies to Aichi target 12 ...

  15. 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.

  16. 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.

  17. Optimization of SCF feeding regimen for ex vivo expansion of cord blood hematopoietic stem cells.

    Science.gov (United States)

    Du, Zheng; Cai, Haibo; Ye, Zhaoyang; Tan, Wen-Song

    2012-12-15

    Stem cell factor (SCF) plays important roles in ex vivo expansion of hematopoietic stem cells (HSCs). In this study, the effects of dose and feeding time of SCF on ex vivo expansion of CD34(+) cells were investigated in serum-free medium supplemented with a cytokine cocktail composed of SCF, thrombopoietin (TPO) and flt3-ligand (FL). Among the four tested doses (0, 5, 50 and 500ng/mL), a SCF dose of 50ng/mL was demonstrated to be most favorable for ex vivo expansion of CD34(+) cells, which resulted in 34.22±10.80 and 8.89±1.25 folds of expansion regarding total cells and CD34(+) cells, respectively. Meanwhile, the specific growth rate of cells, the consumption rate of SCF and the percentage of CD34(+)c-kit(+) cells during the 21-day culture process were analyzed. The results indicated that initial 4-day period was a critical stage for SCF functioning on CD34(+) cells during ex vivo expansion. Based on this, a modified SCF feeding regimen was proposed, in which SCF (50ng/mL) was only supplemented on day 0 in the cytokine cocktail and cells were then fed with TPO and FL till the end of culture. It was found that this SCF feeding regimen could expand CD34(+) cells efficiently, thus providing a cost-effect expansion protocol for HSCs.

  18. Planning water supply under uncertainty - benefits and limitations of RDM, Info-Gap, economic optimization and many-objective optimization

    Science.gov (United States)

    Matrosov, E.; Padula, S.; Huskova, I.; Harou, J. J.

    2012-12-01

    Population growth and the threat of drier or changed climates are likely to increase water scarcity world-wide. A combination of demand management (water conservation) and new supply infrastructure is often needed to meet future projected demands. In this case system planners must decide what to implement, when and at what capacity. Choices can range from infrastructure to policies or a mix of the two, culminating in a complex planning problem. Decision making under uncertainty frameworks can be used to help planners with this planning problem. This presentation introduces, applies and compares four decision making under uncertainty frameworks. The application is to the Thames basin water resource system which includes the city of London. The approaches covered here include least-economic cost capacity expansion optimization (EO), Robust Decision Making (RDM), Info-Gap Decision Theory (Info-gap) and many-objective evolutionary optimization (MOEO). EO searches for the least-economic cost program, i.e. the timing, sizing, and choice of supply-demand management actions/upgrades which meet projected water demands. Instead of striving for optimality, the RDM and Info-gap approaches help build plans that are robust to 'deep' uncertainty in future conditions. The MOEO framework considers multiple performance criteria and uses water systems simulators as a function evaluator for the evolutionary algorithm. Visualizations show Pareto approximate tradeoffs between multiple objectives. In this presentation we detail the application of each framework to the Thames basin (including London) water resource planning problem. Supply and demand options are proposed by the major water companies in the basin. We apply the EO method using a 29 year time horizon and an annual time step considering capital, operating (fixed and variable), social and environmental costs. The method considers all plausible combinations of supply and conservation schemes and capacities proposed by water

  19. 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.

  20. Optimal planning of LEO active debris removal based on hybrid optimal control theory

    Science.gov (United States)

    Yu, Jing; Chen, Xiao-qian; Chen, Li-hu

    2015-06-01

    The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.

  1. 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.

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

    NARCIS (Netherlands)

    Hoffmann, A.L.; Siem, A.Y.; Hertog, D. den; Kaanders, J.H.A.M.; Huizenga, H.

    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 co

  3. On the selection of optimization parameters for an inverse treatment planning replacement of a forward planning technique for prostate cancer.

    Science.gov (United States)

    Hristov, Dimitre H; Moftah, Belal A; Charrois, Colette; Parker, William; Souhami, Luis; Podgorsak, Ervin B

    2002-01-01

    The influence of organ volume sampling, lateral scatter inclusion, and the selection of objectives and constraints on the inverse treatment planning process with a commercial treatment planning system is investigated and suitable parameters are identified for an inverse treatment planning replacement of a clinical forward planning technique for prostate cancer. For the beam geometries of the forward technique, a variable set of parameters is used for the calculation of dose from pencil beams. An optimal set is identified after the evaluation of optimized plans that correspond to different sets of pencil-beam parameters. This set along with a single, optimized set of objectives and constraints is used to perform inverse planning on ten randomly selected patients. The acceptability of the resulting plans is verified by comparisons to the clinical ones calculated with the forward techniques. For the particular commercial treatment planning system, the default values of the pencil beam parameters are found adequate for inverse treatment planning. For all ten patients, the optimized, single set of objectives and constraints results in plans with target coverage comparable to that of the forward plans. Furthermore inverse treatment planning reduces the overall mean rectal and bladder doses by 4.8% and 5.8% of the prescription dose respectively. The study indicates that (i) inverse treatment planning results depend implicitly on the sampling of the dose distribution, (ii) inverse treatment planning results depend on the method used by the dose calculation model to account for scatter, and (iii) for certain sites, a single set of optimization parameters can be used for all patient plans.

  4. PLANNED LEAD TIME OPTIMIZATION IN MATERIAL REQUIREMENT PLANNING ENVIRONMENT FOR MULTILEVEL PRODUCTION SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Faicel HNAIEN; Alexandre DOLGUI; Mohamed-Aly OULD LOULY

    2008-01-01

    This paper deals with the problem of planned lead time calculation in a Material Requirement Planning (MRP) environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered: multi-level serial-production and assembly systems. For the serial production systems (one type of component at each level), a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and several numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.

  5. An improved ant colony optimization approach for optimization of process planning.

    Science.gov (United States)

    Wang, JinFeng; Fan, XiaoLiang; Ding, Haimin

    2014-01-01

    Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

  6. Simulation and optimization models for emergency medical systems planning.

    Science.gov (United States)

    Bettinelli, Andrea; Cordone, Roberto; Ficarelli, Federico; Righini, Giovanni

    2014-01-01

    The authors address strategic planning problems for emergency medical systems (EMS). In particular, the three following critical decisions are considered: i) how many ambulances to deploy in a given territory at any given point in time, to meet the forecasted demand, yielding an appropriate response time; ii) when ambulances should be used for serving nonurgent requests and when they should better be kept idle for possible incoming urgent requests; iii) how to define an optimal mix of contracts for renting ambulances from private associations to meet the forecasted demand at minimum cost. In particular, analytical models for decision support, based on queuing theory, discrete-event simulation, and integer linear programming were presented. Computational experiments have been done on real data from the city of Milan, Italy.

  7. Dosimetric comparison of RapidPlan and manually optimized plans in volumetric modulated arc therapy for prostate cancer.

    Science.gov (United States)

    Kubo, Kazuki; Monzen, Hajime; Ishii, Kentaro; Tamura, Mikoto; Kawamorita, Ryu; Sumida, Iori; Mizuno, Hirokazu; Nishimura, Yasumasa

    2017-07-10

    This study evaluated whether RapidPlan based plans (RP plans) created by a single optimization, are usable in volumetric modulated arc therapy (VMAT) for patients with prostate cancer. We used 51 previously administered VMAT plans to train a RP model. Thirty RP plans were created by a single optimization without planner intervention during optimization. Differences between RP plans and clinical manual optimization (CMO) plans created by an experienced planner for the same patients were analyzed (Wilcoxon tests) in terms of homogeneity index (HI), conformation number (CN), D95%, and D2% to planning target volume (PTV), mean dose, V50Gy, V70Gy, V75Gy, and V78Gy to rectum and bladder, monitor unit (MU), and multi-leaf collimator (MLC) sequence complexity. RP and CMO values for PTV D95%, PTV D2%, HI, and CN were significantly similar (pplans (pplans (pplans created by a single optimization were clinically acceptable in VMAT for patient with prostate cancer. Our simple model could reduce optimization time, independently of planner's skill and knowledge. Copyright © 2017. Published by Elsevier Ltd.

  8. 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.

  9. Efficient Configuration Space Construction and Optimization for Motion Planning

    Directory of Open Access Journals (Sweden)

    Jia Pan

    2015-03-01

    Full Text Available The configuration space is a fundamental concept that is widely used in algorithmic robotics. Many applications in robotics, computer-aided design, and related areas can be reduced to computational problems in terms of configuration spaces. In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: how to efficiently compute an approximate representation of high-dimensional configuration spaces; and how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces. We present new configuration space construction algorithms based on machine learning and geometric approximation techniques. These algorithms perform collision queries on many configuration samples. The collision query results are used to compute an approximate representation for the configuration space, which quickly converges to the exact configuration space. We also present parallel GPU-based algorithms to accelerate the performance of optimization and search computations in configuration spaces. In particular, we design efficient GPU-based parallel k-nearest neighbor and parallel collision detection algorithms and use these algorithms to accelerate motion planning.

  10. SU-F-BRD-10: Improving Plan Delivery Efficiency of Intensity Modulated Proton Plans with Prioritized Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Müller, BS; Wilkens, JJ [Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Munich (Germany); Physik-Department, Technische Universität München, Munich, DE (Germany)

    2015-06-15

    Purpose: To integrate treatment delivery time into plan optimization in spot scanning intensity modulated proton therapy. Utilizing a dedicated research treatment planning system we present an optimization approach to explore the trade-off between the correlated parameters treatment time and plan quality on an astrocytoma patient case. Methods: The planning system is based on prioritized optimization, a stepwise approach of implementing clinical goals. After each optimization step, dosimetric achievements are turned into hard constraints to maintain the achieved plan quality. Prior achievements can be violated by a so-called slip-factor which allows to study possible trade-offs of conflicting goals. Plan quality is obtained in the first two steps, while the third step optimizes delivery efficiency by working on the spot weight distribution via four alternative Methods: elimination of low weighted spots (1), elimination of spots hardly contributing to PTV dose, followed by reoptimization of the resulting smaller optimization problem (2), reduction of spot weights variance within each energy layer (3), and reduction of the overall spot weight sum (4). Treatment times were calculated assuming either constant or variable beam current depending on the lowest spot weight. Results: Delivery efficiency can be improved remarkably without influencing the plan quality. Absolute time savings depend on the utilized method and facility properties. By varying slip-factor and spot reduction limits, a border of worsening quality is detectable for all methods.Deleting low weighted spots by 10% results in a noticeable decrease in minimum target dose. Further reduction results in more heterogeneous dose distributions and insufficient coverage. Option 2 showed constant plan quality for spot reductions of more than 10%. Conclusion: Including treatment time optimization as a final step into prioritized optimization allows for more efficient treatment plans by redistributing the spot

  11. Evolving strategies for optimal care management and plan benefit designs.

    Science.gov (United States)

    Cruickshank, John M

    2012-11-01

    As a prevalent, complex disease, diabetes presents a challenge to managed care. Strategies to optimize type 2 diabetes care management and treatment outcomes have been evolving over the past several years. Novel economic incentive programs (eg, those outlined in the Patient Protection and Affordable Care Act of 2010 that tie revenue from Medicare Advantage plans to the quality of healthcare delivered) are being implemented, as are evidence-based interventions designed to optimize treatment, reduce clinical complications, and lower the total financial burden of the disease. Another step that can improve outcomes is to align managed care diabetes treatment algorithms with national treatment guidelines. In addition, designing the pharmacy benefit to emphasize the overall value of treatment and minimize out-of-pocket expenses for patients can be an effective approach to reducing prescription abandonment. The implementation of emerging models of care that encourage collaboration between providers, support lifestyle changes, and engage patients to become partners in their own treatment also appears to be effective.

  12. Formal-language-theoretic Optimal Path Planning For Accommodation of Amortized Uncertainties and Dynamic Effects

    CERN Document Server

    Chattopadhyay, Ishanu; Ray, Asok

    2010-01-01

    We report a globally-optimal approach to robotic path planning under uncertainty, based on the theory of quantitative measures of formal languages. A significant generalization to the language-measure-theoretic path planning algorithm $\

  13. Optimal mechanical harvester route planning for sugarcane f ield operations using particle swarm optimization

    Directory of Open Access Journals (Sweden)

    Woraya Neungmatcha

    2015-06-01

    Full Text Available Since current agricultural production systems such as the sugarcane supply system in the sugar industry are developing towards larger and more complicated systems, there is consequently increasing use of agricultural machinery. Even though mechanization can help to increase the sugarcane yield, if the mechanical operation efficiency is low, then higher harvest costs and machinery shortages will occur. Global route planning for mechanical harvesters is one of the most important problems in the field of sugarcane harvesting and transporting operations. Improved efficiency and realistic implementation can be achieved by applying advanced planning methods for the execution of field operations, especially considering the field accessibility aspect. To address this issue, participative research was undertaken with a sugar milling company to produce and implement a mixed integer programming model that represents the mechanical harvester route plan. Particle swarm optimization was applied to find a solution to the model, leading to potential cost savings versus schedules produced manually by the mill officer. The model was also applied to explore regional planning options for a more integrated harvesting and transport system.

  14. 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

    2006-12-21

    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.

  15. Grassland Expansion and Establishment Plan for Seatuck National Wildlife Refuge 2004

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This detailed plan provides methods and a time frame for creating 40-60 acres of warm-season grassland at Seatuck National Wildlife Refuge using seed sources, both...

  16. Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge-based solution.

    Science.gov (United States)

    Jiang, Fan; Wu, Hao; Yue, Haizhen; Jia, Fei; Zhang, Yibao

    2017-03-01

    The enhanced dosimetric performance of knowledge-based volumetric modulated arc therapy (VMAT) planning might be jointly contributed by the patient-specific optimization objectives, as estimated by the RapidPlan model, and by the potentially improved Photon Optimizer (PO) algorithm than the previous Progressive Resolution Optimizer (PRO) engine. As PO is mandatory for RapidPlan estimation but optional for conventional manual planning, appreciating the two optimizers may provide practical guidelines for the algorithm selection because knowledge-based planning may not replace the current method completely in a short run. Using a previously validated dose-volume histogram (DVH) estimation model which can produce clinically acceptable plans automatically for rectal cancer patients without interactive manual adjustment, this study reoptimized 30 historically approved plans (referred as clinical plans that were created manually with PRO) with RapidPlan solution (PO plans). Then the PRO algorithm was utilized to optimize the plans again using the same dose-volume constraints as PO plans, where the line objectives were converted as a series of point objectives automatically (PRO plans). On the basis of comparable target dose coverage, the combined applications of new objectives and PO algorithm have significantly reduced the organs-at-risk (OAR) exposure by 23.49-32.72% than the clinical plans. These discrepancies have been largely preserved after substituting PRO for PO, indicating the dosimetric improvements were mostly attributable to the refined objectives. Therefore, Eclipse users of earlier versions may instantly benefit from adopting the model-generated objectives from other RapidPlan-equipped centers, even with PRO algorithm. However, the additional contribution made by the PO relative to PRO accounted for 1.54-3.74%, suggesting PO should be selected with priority whenever available, with or without RapidPlan solution as a purchasable package. Significantly

  17. 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] (and others)

    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.)

  18. 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.

  19. Getting Road Expansion on the Right Track: A Framework for Smart Infrastructure Planning in the Mekong.

    Science.gov (United States)

    Balmford, Andrew; Chen, Huafang; Phalan, Ben; Wang, Mingcheng; O'Connell, Christine; Tayleur, Cath; Xu, Jianchu

    2016-12-01

    The current unprecedented expansion of infrastructure promises to enhance human wellbeing but risks causing substantial harm to natural ecosystems and the benefits they provide for people. A framework for systematically and proactively identifying the likely benefits and costs of such developments is badly needed. Here, we develop and test at the subregional scale a recently proposed global scheme for comparing the potential gains from new roads for food production with their likely impact on biodiversity and ecosystem services. Working in the Greater Mekong-an exceptionally biodiverse subregion undergoing rapid development-we combined maps of isolation from urban centres, yield gaps, and the current area under 17 crops to estimate where and how far road development could in principle help to increase food production without the need for cropland expansion. We overlaid this information with maps summarising the importance of remaining habitats to terrestrial vertebrates and (as examples of major ecosystem services) to global and local climate regulation. This intersection revealed several largely converted yet relatively low-yielding areas (such as central, eastern, and northeastern Thailand and the Ayeyarwady Delta), where narrowing yield gaps by improving transport links has the potential to substantially increase food production at relatively limited environmental cost. Concentrating new roads and road improvements here while taking strong measures to prevent their spread into areas which are still extensively forested (such as northern Laos, western Yunnan, and southwestern Cambodia) could thus enhance rural livelihoods and regional food production while helping safeguard vital ecosystem services and globally significant biological diversity.

  20. Socio-economic and ecological impacts of global protected area expansion plans.

    Science.gov (United States)

    Visconti, Piero; Bakkenes, Michel; Smith, Robert J; Joppa, Lucas; Sykes, Rachel E

    2015-11-05

    Several global strategies for protected area (PA) expansion have been proposed to achieve the Convention on Biological Diversity's Aichi target 11 as a means to stem biodiversity loss, as required by the Aichi target 12. However, habitat loss outside PAs will continue to affect habitats and species, and PAs may displace human activities into areas that might be even more important for species persistence. Here we measure the expected contribution of PA expansion strategies to Aichi target 12 by estimating the extent of suitable habitat available for all terrestrial mammals, with and without additional protection (the latter giving the counterfactual outcome), under different socio-economic scenarios and consequent land-use change to 2020. We found that expanding PAs to achieve representation targets for ecoregions under a Business-as-usual socio-economic scenario will result in a worse prognosis than doing nothing for more than 50% of the world's terrestrial mammals. By contrast, targeting protection towards threatened species can increase the suitable habitat available to over 60% of terrestrial mammals. Even in the absence of additional protection, an alternative socio-economic scenario, adopting progressive changes in human consumption, leads to positive outcomes for mammals globally and to the largest improvements for wide-ranging species.

  1. Sampling-based Algorithms for Optimal Motion Planning

    CERN Document Server

    Karaman, Sertac

    2011-01-01

    During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically opti...

  2. 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)

  3. Spatial planning and residential expansion in the Global South: evidence from Lima, Peru

    NARCIS (Netherlands)

    Fernandez Maldonado, A.M.

    2013-01-01

    Until the 1990s, the Peruvian housing policies exhibited a wide tolerance toward occupation of peripheral land by poor residents, while the state solved the housing demand of the poor allocating large extensions of land for new informal settlements. In front of a very weak spatial planning, the

  4. While Carrefour and others plan expansion,Dutch giant Ahold sells off everything it can find

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    On June 4th, the Dutch retail group Ahold, owner of scandalplagued subsidiary US Foodservice, sold its confectionary store chain Jamin, in what most analysts see as a fire sale to keep the stricken company afloat. And, although the companyrefuses to confirm it, sources insist that it is now planning to do away with the US firm.

  5. Bioluminescence tomography using eigenvectors expansion and iterative solution for the optimized permissible source region.

    Science.gov (United States)

    Naser, Mohamed A; Patterson, Michael S

    2011-11-01

    A reconstruction algorithm for bioluminescence tomography (BLT) has been developed. The algorithm numerically calculates the Green's function at different wavelengths using the diffusion equation and finite element method. The optical properties used in calculating the Green's function are reconstructed using diffuse optical tomography (DOT) and assuming anatomical information is provided by x-ray computed tomography or other methods. A symmetric system of equations is formed using the Green's function and the measured light fluence rate and the resulting eigenvalue problem is solved to get the eigenvectors of this symmetric system of equations. A space can be formed from the eigenvectors obtained and the reconstructed source is written as an expansion of the eigenvectors corresponding to non-zero eigenvalues. The coefficients of the expansion are found to obtain the reconstructed BL source distribution. The problem is solved iteratively by using a permissible source region that is shrunk by removing nodes with low probability to contribute to the source. Throughout this process the permissible region shrinks from the entire object to just a few nodes. The best estimate of the reconstructed source is chosen that which minimizes the difference between the calculated and measured light fluence rates. 3D simulations presented here show that the reconstructed source is in good agreement with the actual source in terms of locations, magnitudes, sizes, and total powers for both localized multiple sources and large inhomogeneous source distributions.

  6. The effect of gantry spacing resolution on plan quality in a single modulated arc optimization.

    Science.gov (United States)

    Mihaylov, Ivaylo B; Curran, Bruce; Sternick, Edward

    2011-11-15

    Volumetric-modulated arc technique (VMAT) is an efficient form of IMRT delivery. It is advantageous over conventional IMRT in terms of treatment delivery time. This study investigates the relation between the number of segments and plan quality in VMAT optimization for a single modulated arc. Five prostate, five lung, and five head-and-neck (HN) patient plans were studied retrospectively. For each case, four VMAT plans were generated. The plans differed only in the number of control points used in the optimization process. The control points were spaced 2°, 3°, 4°, and 6° apart, respectively. All of the optimization parameters were the same among the four schemes. The 2° spacing plan was used as a reference to which the other three plans were compared. The plan quality was assessed by comparison of dose indices (DIs) and generalized equivalent uniform doses (gEUDs) for targets and critical structures. All optimization schemes generated clinically acceptable plans. The differences between the majority of reference and compared DIs and gEUDs were within 3%. DIs and gEUDs which differed in excess of 3% corresponded to dose levels well below the organ tolerances. The DI and the gEUD differences increased with an increase in plan complexity from prostates to HNs. Optimization with gantry spacing resolution of 4° seems to be a very balanced alternative between plan quality and plan complexity.

  7. A Multi-Criteria Framework with Voxel-Dependent Parameters for Radiotherapy Treatment Plan Optimization

    CERN Document Server

    Zarepisheh, Masoud; Li, Nan; Jia, Xun; Jiang, Steve B

    2012-01-01

    In a 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 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. To answer questions related to this problem, we establish in this work a new mathematical framework equipped with two theorems. 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 different effects of adjusting weighting factors versus reference doses in the optimization process. 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 sin...

  8. Transmission expansion planning under increased uncertainties, towards efficient and sustainable power systems

    NARCIS (Netherlands)

    Ciupuliga, A.R.

    2013-01-01

    The ongoing liberalization process around the world has led to the emergence of energy markets, facilitating more international trade between countries making the best use of energy resources and optimizing overall power systems. Consequently, inter-area power exchanges have significantly increased

  9. Transmission expansion planning under increased uncertainties, towards efficient and sustainable power systems

    NARCIS (Netherlands)

    Ciupuliga, A.R.

    2013-01-01

    The ongoing liberalization process around the world has led to the emergence of energy markets, facilitating more international trade between countries making the best use of energy resources and optimizing overall power systems. Consequently, inter-area power exchanges have significantly increased

  10. Optimizing harvest of corn stover fractions based on overall sugar yields following ammonia fiber expansion pretreatment and enzymatic hydrolysis

    Directory of Open Access Journals (Sweden)

    Dale Bruce E

    2009-11-01

    Full Text Available Abstract Background Corn stover composition changes considerably throughout the growing season and also varies between the various fractions of the plant. These differences can impact optimal pretreatment conditions, enzymatic digestibility and maximum achievable sugar yields in the process of converting lignocellulosics to ethanol. The goal of this project was to determine which combination of corn stover fractions provides the most benefit to the biorefinery in terms of sugar yields and to determine the preferential order in which fractions should be harvested. Ammonia fiber expansion (AFEX pretreatment, followed by enzymatic hydrolysis, was performed on early and late harvest corn stover fractions (stem, leaf, husk and cob. Sugar yields were used to optimize scenarios for the selective harvest of corn stover assuming 70% or 30% collection of the total available stover. Results The optimal AFEX conditions for all stover fractions, regardless of harvest period, were: 1.5 (g NH3 g-1 biomass; 60% moisture content (dry-weight basis; dwb, 90°C and 5 min residence time. Enzymatic hydrolysis was conducted using cellulase, β-glucosidase, and xylanase at 31.3, 41.3, and 3.1 mg g-1 glucan, respectively. The optimal harvest order for selectively harvested corn stover (SHCS was husk > leaf > stem > cob. This harvest scenario, combined with optimal AFEX pretreatment conditions, gave a theoretical ethanol yield of 2051 L ha-1 and 912 L ha-1 for 70% and 30% corn stover collection, respectively. Conclusion Changing the proportion of stover fractions collected had a smaller impact on theoretical ethanol yields (29 - 141 L ha-1 compared to the effect of altering pretreatment and enzymatic hydrolysis conditions (150 - 462 L ha-1 or harvesting less stover (852 - 1139 L ha-1. Resources may be more effectively spent on improving sustainable harvesting, thereby increasing potential ethanol yields per hectare harvested, and optimizing biomass processing rather than

  11. A Numerical Approach for Solving Optimal Control Problems Using the Boubaker Polynomials Expansion Scheme

    Directory of Open Access Journals (Sweden)

    B. Kafash

    2014-04-01

    Full Text Available In this paper, we present a computational method for solving optimal control problems and the controlled Duffing oscillator. This method is based on state parametrization. In fact, the state variable is approximated by Boubaker polynomials with unknown coefficients. The equation of motion, performance index and boundary conditions are converted into some algebraic equations. Thus, an optimal control problem converts to a optimization problem, which can then be solved easily. By this method, the numerical value of the performance index is obtained. Also, the control and state variables can be approximated as functions of time. Convergence of the algorithms is proved. Numerical results are given for several test examples to demonstrate the applicability and efficiency of the method.

  12. CDIO Based Optimization of Urban Planning Personnel Training Courses in Forestry Universities

    Institute of Scientific and Technical Information of China (English)

    Ming; SUN; Jun; ZHANG; Jun; DONG; Bing; CHANG

    2014-01-01

    On the basis of analyzing existing course system of urban planning discipline,this paper came up with a framework for optimization of urban planning personnel training mode and course system,oriented towards training practical engineering personnel and based on CDIO engineering education and teaching platform. Then it made empirical study on setting of the urban planning discipline in Northeast Forestry University. It proposed changing the original "3 + 2" course system,exploring and optimizing the course system,improving teaching effect of urban planning personnel training courses,and raising planning and design ability of students.

  13. Using Optimization to Improve NASA Extravehicular Activity Planning

    Science.gov (United States)

    2012-09-01

    planning process is required to prepare for each highly choreographed EVA operation. The current planning process relies heavily upon time-consuming...process is required to prepare for each highly choreographed EVA operation. The current planning process relies heavily upon time-consuming heuristic...multitude of sources. As a result, EVA plans must be highly choreographed to achieve the maximum value from each operation. Since the advent of EVA

  14. 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.

  15. 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.

  16. Adaptive Transmission Planning: Implementing a New Paradigm for Managing Economic Risks in Grid Expansion

    Energy Technology Data Exchange (ETDEWEB)

    Hobbs, Benjamin F.; Xu, Qingyu; Ho, Jonathan; Donohoo, Pearl; Kasina, Saamrat; Ouyang, Jasmine; Park, Sang Woo; Eto, Joseph; Satyal, Vijay

    2016-07-01

    The problem of whether, where, when, and what types of transmission facilities to build in terms of minimizing costs and maximizing net economic benefits has been a challenge for the power industry from the beginning-ever since Thomas Edison debated whether to create longer dc distribution lines (with their high losses) or build new power stations in expanding his urban markets. Today's planning decisions are far more complex, as grids cover the continent and new transmission, generation, and demand-side technologies emerge.

  17. Planning of medium-voltage networks considering optimized power factor control of distributed generators; Planung von Mittelspannungsnetzen unter Beruecksichtigung von Blindleistungssteuerung dezentraler Erzeugungsanlagen

    Energy Technology Data Exchange (ETDEWEB)

    Rotering, Niklas; Schroeders, Christian; Moser, Albert [RWTH Aachen (Germany). IAEW

    2011-07-01

    Distributed generation causes new challenges in medium voltage networks. Especially voltage stability is becoming an issue. Conventional planning measures, like network expansion, can be used to address these challenges but they should planned with great care due to their high costs. Power factor control of distributed generators is an alternative to such measures. Therefore it should also be considered in long term distribution network planning. It is the purpose of this paper to present a new approach for long term medium-voltage network optimization that integrates near optimal power factor control. The structural optimization is heuristic and based on a Delaunay triangulation in combination with an ant colony algorithm. Power factor control is predicated on dynamic programming. It is shown how near optimal results can easily be realized under German law with present technologies. A case study illustrates the impacts and advantages of an integrated planning approach. The integrated optimization results in network costs that are 2.5% lower than the costs of the best topology found by conventional planning. (orig.)

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    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. Impact of dose calculation accuracy during optimization on lung IMRT plan quality.

    Science.gov (United States)

    Li, Ying; Rodrigues, Anna; Li, Taoran; Yuan, Lulin; Yin, Fang-Fang; Wu, Q Jackie

    2015-01-08

    The purpose of this study was to evaluate the effect of dose calculation accuracy and the use of an intermediate dose calculation step during the optimization of intensity-modulated radiation therapy (IMRT) planning on the final plan quality for lung cancer patients. This study included replanning for 11 randomly selected free-breathing lung IMRT plans. The original plans were optimized using a fast pencil beam convolution algorithm. After optimization, the final dose calculation was performed using the analytical anisotropic algorithm (AAA). The Varian Treatment Planning System (TPS) Eclipse v11, includes an option to perform intermediate dose calculation during optimization using the AAA. The new plans were created using this intermediate dose calculation during optimization with the same planning objectives and dose constraints as in the original plan. Differences in dosimetric parameters for the planning target volume (PTV) dose coverage, organs-at-risk (OARs) dose sparing, and the number of monitor units (MU) between the original and new plans were analyzed. Statistical significance was determined with a p-value of less than 0.05. All plans were normalized to cover 95% of the PTV with the prescription dose. Compared with the original plans, the PTV in the new plans had on average a lower maximum dose (69.45 vs. 71.96Gy, p = 0.005), a better homogeneity index (HI) (0.08 vs. 0.12, p = 0.002), and a better conformity index (CI) (0.69 vs. 0.59, p = 0.003). In the new plans, lung sparing was increased as the volumes receiving 5, 10, and 30 Gy were reduced when compared to the original plans (40.39% vs. 42.73%, p = 0.005; 28.93% vs. 30.40%, p = 0.001; 14.11%vs. 14.84%, p = 0.031). The volume receiving 20 Gy was not significantly lower (19.60% vs. 20.38%, p = 0.052). Further, the mean dose to the lung was reduced in the new plans (11.55 vs. 12.12 Gy, p = 0.024). For the esophagus, the mean dose, the maximum dose, and the volumes receiving 20 and 60 Gy were lower in

  20. A graph-based ant colony optimization approach for process planning.

    Science.gov (United States)

    Wang, JinFeng; Fan, XiaoLiang; Wan, Shuting

    2014-01-01

    The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach.

  1. 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.

  2. Considering Renewables in Capacity Expansion Models: Capturing Flexibility with Hourly Dispatch

    Energy Technology Data Exchange (ETDEWEB)

    Barrows, Clayton; Mai, Trieu; Hale, Elaine; Lopez, Anthony; Eurek, Kelly

    2015-07-03

    The Resource Planning Model co-optimizes dispatch and capacity expansion using a simplified, chronological dispatch period representation and high-resolution resource, load and infrastructure data. The computational tractability of capacity expansion models depends on model simplifications. We demonstrate the effects of various dispatch period representations on model results using the Resource Planning Model.

  3. OPTIMAL MOTION PLANNING FOR A RIGID SPACECRAFT WITH TWO MOMENTUM WHEELS USING QUASI-NEWTON METHOD

    Institute of Scientific and Technical Information of China (English)

    Ge Xinsheng; Zhang Qizhi; Chen LiQun

    2006-01-01

    An optimal motion planning scheme based on the quasi-Newton method is proposed for a rigid spacecraft with two momentum wheels. A cost functional is introduced to incorporate the control energy, the final state errors and the constraints on states. The motion planning for determining control inputs to minimize the cost functional is formulated as a nonlinear optimal control problem. Using the control parametrization, one can transform the infinite dimensional optimal control problem to a finite dimensional one that is solved via the quasi-Newton methods for a feasible trajectory which satisfies the nonholonomic constraint. The optimal motion planning scheme was applied to a rigid spacecraft with two momentum wheels. The simulation results show the effectiveness of the proposed optimal motion planning scheme.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

    2009-01-15

    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

  5. An optimization model of UAV route planning for road segment surveillance

    Institute of Scientific and Technical Information of China (English)

    刘晓锋; 关志伟; 宋裕庆; 陈大山

    2014-01-01

    Unmanned aerial vehicle (UAV) was introduced to take road segment traffic surveillance. Considering the limited UAV maximum flight distance, UAV route planning problem was studied. First, a multi-objective optimization model of planning UAV route for road segment surveillance was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem. At last, a UAV flight experiment was conducted to test UAV route planning effect, and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning. The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%, respectively. Additionally, shortening or extending the length of road segments has different impacts on UAV route planning.

  6. 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

  7. The path planning of UAV based on orthogonal particle swarm optimization

    Science.gov (United States)

    Liu, Xin; Wei, Haiguang; Zhou, Chengping; Li, Shujing

    2013-10-01

    To ensure the attack mission success rate, a trajectory with high survivability and accepted path length and multiple paths with different attack angles must be planned. This paper proposes a novel path planning algorithm based on orthogonal particle swarm optimization, which divides population individual and speed vector into independent orthogonal parts, velocity and individual part update independently, this improvement advances optimization effect of traditional particle swarm optimization in the field of path planning, multiple paths are produced by setting different attacking angles, this method is simulated on electronic chart, the simulation result shows the effect of this method.

  8. 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.

    2016-06-01

    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

  9. Optimal Model and Solution of Railway Hub Shift Working Plan

    Institute of Scientific and Technical Information of China (English)

    He Shiwei; Zhu Songnian; Lin Boliang

    1996-01-01

    Aiming at decreasing the hub transportation costs, a railway hub shift working plan in terms of multicommodity network flow model is set up for considering the coordination of freight working, train working and locomotive working plans. The solution and the calculating results are also introduced.

  10. 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....

  11. Planning Optimal Paths for Multi-agent Systems on Graphs

    CERN Document Server

    Yu, Jingjin

    2012-01-01

    For the problem of moving a set of agents on a connected graph with unit edge distance to agent-specific goal locations, free of collisions, we propose two multiflow based integer linear programming (ILP) models that find time optimal and distance optimal solutions, respectively. The resulting algorithms from our ILP models are complete and guaranteed to yield true optimal solutions. Focusing on the time optimal formulation, we evaluate its performance, both as a stand alone algorithm and as a generic heuristic for quickly solving large problem instances. The computational results confirm the effectiveness of our method.

  12. Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming

    Institute of Scientific and Technical Information of China (English)

    Xiong LUO; Xiaoping FAN; Heng ZHANG; Tefang CHEN

    2004-01-01

    Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots.The performance indexes used in optimal trajectory planning are classified into two main categories:optimum traveling time and optimum mechanical energy of the actuators.The current trajectory planning algorithms are designed based on one of the above two performance indexes.So far,there have been few planning algorithms designed to satisfy two performance indexes simultaneously.On the other hand,some deficiencies arise in the existing integrated optimization algorithms of trajectory planning.In order to overcome those deficiencies,the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators.In the algorithm,two object functions are designed based on the specific weight coefficient method and "ideal point" strategy.Moreover,based on the features of optimization problem,the intensified evolutionary programming is proposed to solve the corresponding optimization model.Especially,for the Stanford Robot,the high-quality solutions are found at a lower cost.

  13. 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

  14. Application of particle swarm optimization in path planning of mobile robot

    Science.gov (United States)

    Wang, Yong; Cai, Feng; Wang, Ying

    2017-08-01

    In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

  15. Globally Optimal Path Planning with Anisotropic Running Costs

    Science.gov (United States)

    2013-03-01

    Proceedings of the American Control Conference , pp...Jacques, D. R. & Pachter, M. (2002) Air vehicle optimal trajectories between two radars, in Proceedings of the American Control Conference . Pachter...M. & Hebert, J. (2001) Optimal aircraft trajectories for radar exposure mini- mization, in Proceedings of the American Control Conference .

  16. 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)

  17. Cost Optimal Reliability Based Inspection and Replacement Planning of Piping Subjected to CO2 Corrosion

    DEFF Research Database (Denmark)

    Hellevik, S. G.; Langen, I.; Sørensen, John Dalsgaard

    1999-01-01

    A methodology for cost optimal reliability based inspection and replacement planning of piping subjected to CO2 corrosion is described. Both initial (design phase) and in-service planning are dealt with. The methodology is based on the application of methods for structural reliability analysis...... within the framework of Bayesian decision theory. The planning problem is formulated as an optimization problem where the expected lifetime costs are minimized with a constraint on the minimum acceptable reliability level. The optimization parameters are the number of inspections in the expected lifetime......, the inspection times and methods. In the design phase the nominal design wall thickness is also treated as an optimization parameter. The most important benefits gained through the application of the methodology are consistent evaluation of the consequences of different inspection and replacement plans...

  18. Incorporating High-Speed, Optimizing, Interleaving, Configurable/Composable Scheduling into NASA's EUROPA Planning Architecture Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced, robust, autonomous planning systems have not focused on the scheduling decisions made by the planner. And high quality, optimizing schedulers have rarely...

  19. A moment-based approach for DVH-guided radiotherapy treatment plan optimization

    Science.gov (United States)

    Zarepisheh, M.; Shakourifar, M.; Trigila, G.; Ghomi, P. S.; Couzens, S.; Abebe, A.; Noreña, L.; Shang, W.; Jiang, Steve B.; Zinchenko, Y.

    2013-03-01

    The dose-volume histogram (DVH) is a clinically relevant criterion to evaluate the quality of a treatment plan. It is hence desirable to incorporate DVH constraints into treatment plan optimization for intensity modulated radiation therapy. Yet, the direct inclusion of the DVH constraints into a treatment plan optimization model typically leads to great computational difficulties due to the non-convex nature of these constraints. To overcome this critical limitation, we propose a new convex-moment-based optimization approach. Our main idea is to replace the non-convex DVH constraints by a set of convex moment constraints. In turn, the proposed approach is able to generate a Pareto-optimal plan whose DVHs are close to, or if possible even outperform, the desired DVHs. In particular, our experiment on a prostate cancer patient case demonstrates the effectiveness of this approach by employing two and three moment formulations to approximate the desired DVHs.

  20. Double global optimum genetic algorithm-particle swarm optimization-based welding robot path planning

    Science.gov (United States)

    Wang, Xuewu; Shi, Yingpan; Ding, Dongyan; Gu, Xingsheng

    2016-02-01

    Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm-particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.

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

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M.H.

    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...

  2. 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...

  3. Optimization of Map Compilation for County-level Land Consolidation Planning

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Based on practice of the land consolidation planning in Changfeng County of Hefei City,taking full account of reality of land consolidation and its significance as livelihood project,we analyzed map compilation procedure.In combination with actual effect of land consolidation,we carried out consolidation assessment of same elements by overall planning method,and optimized the map compilation for county-level land consolidation planning.Results show that planning map of land consolidation potential is to be improved and legends should be merged.After consolidation of legends,it is convenient to apply in potential planning map and solve complicated problem of reading maps.

  4. METROSIM: Metroplex-Wide Flight Planning and Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The key innovation of this effort is the development of a Metroplex-based arrival, departure, and surface optimization system which we call MetroSim. Linking with...

  5. METROSIM: Metroplex-Wide Flight Planning and Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — MetroSim is a Metroplex-based arrival, departure, and surface optimization. Linking with both the NASA-developed Traffic Management Advisor (TMA) tool as well as the...

  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 practice. The

  7. 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 practice. The tremendo

  8. 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 practice. The tremendo

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

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M. H.; 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...

  10. Use of plan quality degradation to evaluate tradeoffs in delivery efficiency and clinical plan metrics arising from IMRT optimizer and sequencer compromises.

    Science.gov (United States)

    Wilkie, Joel R; Matuszak, Martha M; Feng, Mary; Moran, Jean M; Fraass, Benedick A

    2013-07-01

    Plan degradation resulting from compromises made to enhance delivery efficiency is an important consideration for intensity modulated radiation therapy (IMRT) treatment plans. IMRT optimization and/or multileaf collimator (MLC) sequencing schemes can be modified to generate more efficient treatment delivery, but the effect those modifications have on plan quality is often difficult to quantify. In this work, the authors present a method for quantitative assessment of overall plan quality degradation due to tradeoffs between delivery efficiency and treatment plan quality, illustrated using comparisons between plans developed allowing different numbers of intensity levels in IMRT optimization and/or MLC sequencing for static segmental MLC IMRT plans. A plan quality degradation method to evaluate delivery efficiency and plan quality tradeoffs was developed and used to assess planning for 14 prostate and 12 head and neck patients treated with static IMRT. Plan quality was evaluated using a physician's predetermined "quality degradation" factors for relevant clinical plan metrics associated with the plan optimization strategy. Delivery efficiency and plan quality were assessed for a range of optimization and sequencing limitations. The "optimal" (baseline) plan for each case was derived using a clinical cost function with an unlimited number of intensity levels. These plans were sequenced with a clinical MLC leaf sequencer which uses >100 segments, assuring delivered intensities to be within 1% of the optimized intensity pattern. Each patient's optimal plan was also sequenced limiting the number of intensity levels (20, 10, and 5), and then separately optimized with these same numbers of intensity levels. Delivery time was measured for all plans, and direct evaluation of the tradeoffs between delivery time and plan degradation was performed. When considering tradeoffs, the optimal number of intensity levels depends on the treatment site and on the stage in the process

  11. A Hybrid Analytical/Simulation Modeling Approach for Planning and Optimizing Mass Tactical Airborne Operations

    Science.gov (United States)

    1995-05-01

    A HYBRID ANALYTICAL/ SIMULATION MODELING APPROACH FOR PLANNING AND OPTIMIZING MASS TACTICAL AIRBORNE OPERATIONS by DAVID DOUGLAS BRIGGS M.S.B.A...COVERED MAY 1995 TECHNICAL REPORT THESIS 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS A HYBRID ANALYTICAL SIMULATION MODELING APPROACH FOR PLANNING AND...are present. Thus, simulation modeling presents itself as an excellent alternate tool for planning because it allows for the modeling of highly complex

  12. IMRT treatment planning for prostate cancer using prioritized prescription optimization and mean-tail-dose functions

    OpenAIRE

    2008-01-01

    Treatment planning for intensity modulated radiation therapy (IMRT) is challenging due to both the size of the computational problems (thousands of variables and constraints) and the multi-objective, imprecise nature of the goals. We apply hierarchical programming to IMRT treatment planning. In this formulation, treatment planning goals/objectives are ordered in an absolute hierarchy, and the problem is solved from the top-down such that more important goals are optimized in turn. After each ...

  13. 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.

  14. 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.

  15. 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.

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

    DEFF Research Database (Denmark)

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

    2008-01-01

    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......, 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...

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

    DEFF Research Database (Denmark)

    Ramírez, José G. Rangel; Sørensen, John Dalsgaard

    2008-01-01

    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 coming years. The support structure for offshore wind turbines is typically a steel structure consisting of a tower......, 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 on risk-based inspection planning methods used for oil & gas installations, a framework...

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

    DEFF Research Database (Denmark)

    Ramírez, José G. Rangel; Sørensen, John Dalsgaard

    2008-01-01

    and monopile, tripod or jacket type foundation. Monopiles are at present the most typical foundation, but tripods and jackets are expected to be used in the future at larger water depths. The support structures are facing deterioration processes such as fatigue and corrosion. To ‘control' this deterioration......, 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 on risk-based inspection planning methods used for oil & gas installations, a framework...

  19. Northern Arabian Sea Circulation - Autonomous Research: Optimal Planning Systems (NASCar-OPS)

    Science.gov (United States)

    2015-09-30

    Optimal Planning Systems (NASCar-OPS) Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering Center for Ocean Science and Engineering... system design and for adaptive sampling during sea operations , using advanced Bayesian information theoretic approaches - Improve the understanding of...modeling, both for real-time sea operations and for optimized re-analyses - Collaborate and transfer data, expertise, approaches, algorithms and

  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. 3D conformal planning using low segment multi-criteria IMRT optimization

    CERN Document Server

    Khan, Fazal

    2014-01-01

    Purpose: To evaluate automated multicriteria optimization (MCO)-- designed for intensity modulated radiation therapy (IMRT), but invoked with limited segmentation -- to efficiently produce high quality 3D conformal treatment (3D-CRT) plans. Methods: Ten patients previously planned with 3D-CRT were replanned with a low-segment inverse multicriteria optimized technique. The MCO-3D plans used the same number of beams, beam geometry and machine parameters of the corresponding 3D plans, but were limited to an energy of 6 MV. The MCO-3D plans were optimized using a fluence-based MCO IMRT algorithm and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean doses to individual organs at risk (OARs), mean doses to combined OARs, homogeneity indexes (HI), monitor units (MUs), physician preference, and qualitative assessments of planning time and plan customizability. Results: The MCO-3D plans significantly reduced the OAR mean doses and monitor unit...

  2. An optimal setup planning selection approach in a complex product machining process

    Science.gov (United States)

    Zhu, Fang

    2011-10-01

    Setup planning has very important influence on the product quality in a Complex Product Machining Process (CPMP). Part production in a CPMP involves multiple setup plans, which will lead into variation propagation and lead to extreme complexity in final product quality. Current approaches of setup planning in a CPMP are experience-based that lead to adopt higher machining process cost to ensure the final product quality, and most approaches are used for a single machining process. This work attempts to solve those challenging problems and aims to develop a method to obtain an optimal setup planning in a CPMP, which can satisfies the quality specifications and minimizes the expected value of the sum of machining costs. To this end, a machining process model is established to describe the variation propagation effect of setup plan throughout all stages in a CPMP firstly and then a quantitative setup plan evaluation methods driven by cost constraint is proposed to clarify what is optimality of setup plans. Based on the above procedures, an optimal setup planning is obtained through a dynamic programming solver. At last, a case study is provided to illustrate the validity and the significance of the proposed setup planning selective method.

  3. 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)

  4. Global optimal path planning for mobile robot based on improved Dijkstra algorithm and ant system algorithm

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

  5. A comparison of inverse optimization algorithms for HDR/PDR prostate brachytherapy treatment planning.

    Science.gov (United States)

    Dinkla, Anna M; van der Laarse, Rob; Kaljouw, Emmie; Pieters, Bradley R; Koedooder, Kees; van Wieringen, Niek; Bel, Arjan

    2015-01-01

    Graphical optimization (GrO) is a common method for high-dose-rate/pulsed-dose-rate (PDR) prostate brachytherapy treatment planning. New methods performing inverse optimization of the dose distribution have been developed over the past years. The purpose is to compare GrO and two established inverse methods, inverse planning simulated annealing (IPSA) and hybrid inverse treatment planning and optimization (HIPO), and one new method, enhanced geometric optimization-interactive inverse planning (EGO-IIP), in terms of speed and dose-volume histogram (DVH) parameters. For 26 prostate cancer patients treated with a PDR brachytherapy boost, an experienced treatment planner optimized the dose distributions using four different methods: GrO, IPSA, HIPO, and EGO-IIP. Relevant DVH parameters (prostate-V100%, D90%, V150%; urethra-D(0.1cm3) and D(1.0cm3); rectum-D(0.1cm3) and D(2.0cm3); bladder-D(2.0cm3)) were evaluated and their compliance to the constraints. Treatment planning time was also recorded. All inverse methods resulted in shorter planning time (mean, 4-6.7 min), as compared with GrO (mean, 7.6 min). In terms of DVH parameters, none of the inverse methods outperformed the others. However, all inverse methods improved on compliance to the planning constraints as compared with GrO. On average, EGO-IIP and GrO resulted in highest D90%, and the IPSA plans resulted in lowest bladder D2.0cm3 and urethra D(1.0cm3). Inverse planning methods decrease planning time as compared with GrO for PDR/high-dose-rate prostate brachytherapy. DVH parameters are comparable for all methods. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

  6. Use of plan quality degradation to evaluate tradeoffs in delivery efficiency and clinical plan metrics arising from IMRT optimizer and sequencer compromises

    Science.gov (United States)

    Wilkie, Joel R.; Matuszak, Martha M.; Feng, Mary; Moran, Jean M.; Fraass, Benedick A.

    2013-01-01

    Purpose: Plan degradation resulting from compromises made to enhance delivery efficiency is an important consideration for intensity modulated radiation therapy (IMRT) treatment plans. IMRT optimization and/or multileaf collimator (MLC) sequencing schemes can be modified to generate more efficient treatment delivery, but the effect those modifications have on plan quality is often difficult to quantify. In this work, the authors present a method for quantitative assessment of overall plan quality degradation due to tradeoffs between delivery efficiency and treatment plan quality, illustrated using comparisons between plans developed allowing different numbers of intensity levels in IMRT optimization and/or MLC sequencing for static segmental MLC IMRT plans. Methods: A plan quality degradation method to evaluate delivery efficiency and plan quality tradeoffs was developed and used to assess planning for 14 prostate and 12 head and neck patients treated with static IMRT. Plan quality was evaluated using a physician's predetermined “quality degradation” factors for relevant clinical plan metrics associated with the plan optimization strategy. Delivery efficiency and plan quality were assessed for a range of optimization and sequencing limitations. The “optimal” (baseline) plan for each case was derived using a clinical cost function with an unlimited number of intensity levels. These plans were sequenced with a clinical MLC leaf sequencer which uses >100 segments, assuring delivered intensities to be within 1% of the optimized intensity pattern. Each patient's optimal plan was also sequenced limiting the number of intensity levels (20, 10, and 5), and then separately optimized with these same numbers of intensity levels. Delivery time was measured for all plans, and direct evaluation of the tradeoffs between delivery time and plan degradation was performed. Results: When considering tradeoffs, the optimal number of intensity levels depends on the treatment

  7. 含风电场的双层电源规划%Bi-level Generation Expansion Planning With Large-Scale Wind Farms

    Institute of Scientific and Technical Information of China (English)

    张节潭; 苗淼; 范宏; 程浩忠; 张洪平; 姚良忠; Bazargan Masoud

    2011-01-01

    The impacts of wind farms on system peak regulation, frequency regulation, and environmental protection are analyzed. To take above-mentioned impacts of wind farms into account and the impact of different generation price on investment decision, based on the idea of decomposition coordination, a bi-level generation expansion planning model for power grid containing large-scale wind farms is built. In this model the net earning maximization and the constraints of peak regulation, frequency regulation and environment protection are considered, in addition the influence of the differences among pool purchase prices on generation expansion planning is taken into account. The upper-level planning is a power source investment decision-making problem, so the total revenue maximization of gencos is taken as objective function and the decision variables are the construction time of the power plants to be build and the numbers of the generators to be installed in these plants, the retirement time of existing power plants and numbers of generators in these plants; the lower-level planning is a production optimization decision problem that can be divided into two subproblems, namely the maintenance scheduling and stochastic production simulation, and the decision variables are maintenance time intervals of generating units and the operating positions of generating units on load curve. To solve the proposed model, the plant growth simulation algorithm is integrated with minimum cumulative risk algorithm and equivalent energy and frequency function method is adopted. The feasibility and efficiency of the proposed model are verified by the results of numerical example.%按分解协调的思想,建立了考虑调峰、调频及环保约束的净收益最大化双层电源规划模型,计及了上网电价差异对电源规划的影响。上层规划为电源投资决策问题,以发电商总收益最大为目标函数,决策变量是待选电厂的投建时间和台数以

  8. 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...... industrial time and quality requirements. Our approach combines an integer programming model for assigning groups of containers to storage areas of the vessel over multiple ports, and a constraint programming and local search procedure for stowing individual containers....

  9. Application of Taboo Search and Genetic Algorithm in planning and optimization of UMTS radio networks

    OpenAIRE

    Jalili, B; Dianati, M.

    2010-01-01

    Planning and optimization of 3G networks is more than just frequency allocation and coverage planning, due to the nature of WCDMA coding. It usually involves solution of an NP-Hard problem. In this paper we propose an effective method for optimizing the Common Pilot Channel (CPICH) transmit power, along with maximizing the number of served users and minimizing the number of cell sites and compare use of two meta-heuristic methods: Taboo Search (TS) and Genetic Algorithm (GA) in planning and o...

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

    DEFF Research Database (Denmark)

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

    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...... industrial time and quality requirements. Our approach combines an integer programming model for assigning groups of containers to storage areas of the vessel over multiple ports, and a constraint programming and local search procedure for stowing individual containers....

  11. Integrated Multidisciplinary Optimization of Rotorcraft: A Plan for Development

    Science.gov (United States)

    1989-05-01

    that of thickness noise, strongest in the rotor plane. Although observed experimentally, due to nonlinear transonic effects, this source is not as well...frequencies. The plan for validating the components of the design process was described and the strategy for overall validation of the design methology was

  12. 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...

  13. Optimization and Robustness in Planning and Scheduling Problems. Application to Container Terminals

    OpenAIRE

    Rodríguez Molins, Mario

    2015-01-01

    Despite the continuous evolution in computers and information technology, real-world combinatorial optimization problems are NP-problems, in particular in the domain of planning and scheduling. Thus, although exact techniques from the Operations Research (OR) field, such as Linear Programming, could be applied to solve optimization problems, they are difficult to apply in real-world scenarios since they usually require too much computational time, i.e: an optimized solution is ...

  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

    , 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...... and the size of the station) which leads to an improvement in the algorithm functionality and enhances quality of solution. The genetic algorithm and improved version of conventional particle swarm optimization algorithm will also be compared with a conventional genetic algorithm and particle swarm...... optimization. Through simulation studies on a real time system of Allahabad city, the superior performance of the aforementioned technique with respect to genetic algorithm and particle swarm optimization in terms of improvement in voltage profile and quality....

  15. 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...... probability and associated sensitivity factors are computed by first-order reliability methods. Inspection reliability is included through a pod (probability of detection) curve. Optimization variables are structural design parameters, inspection times and qualities. The total expected cost of design......, inspection, repair and failure is minimized with a constraint on the life time reliability....

  16. 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.

  17. 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

  18. MO-B-BRB-03: Systems Engineering Tools for Treatment Planning Process Optimization in Radiation Medicine

    Energy Technology Data Exchange (ETDEWEB)

    Kapur, A. [Long Island Jewish Medical Center (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

  19. A Multi-pipe Path Planning by Modified Ant Colony Optimization

    Institute of Scientific and Technical Information of China (English)

    QU Yan-feng; JIANG Dan; LIU Bin

    2011-01-01

    Path planning in 3D geometry space is used to find an optimal path in the restricted environment, according to a certain evaluation criteria. To solve the problem of long searching time and slow solving speed in 3D path planning, a modified ant colony optimization is proposed in this paper. Firstly, the grid method for environment modeling is adopted. Heuristic information is connected with the planning space. A semi-iterative global pheromone update mechanism is proposed. Secondly, the optimal ants mutate the paths to improve the diversity of the algorithm after a defined iterative number. Thirdly, co-evolutionary algorithm is used. Finally, the simulation result shows the effectiveness of the proposed algorithm in solving the problem of 3D pipe path planning.

  20. Optimal Trajectory Planning and Coordinated Tracking Control Method of Tethered Space Robot Based on Velocity Impulse

    Directory of Open Access Journals (Sweden)

    Panfeng Huang

    2014-09-01

    Full Text Available The tethered space robot (TSR is a new concept of space robot which consists of a robot platform, space tether and operation robot. This paper presents a multi-objective optimal trajectory planning and a coordinated tracking control scheme for TSR based on velocity impulse in the approaching phase. Both total velocity impulse and flight time are included in this optimization. The non-dominated sorting genetic algorithm is employed to obtain the optimal trajectory Pareto solution using the TSR dynamic model and optimal trajectory planning model. The coordinated tracking control scheme utilizes optimal velocity impulse. Furthermore, the PID controller is designed in order to compensate for the distance measurement errors. The PID control force is optimized and distributed to thrusters and the space tether using a simulated annealing algorithm. The attitude interferential torque of the space tether is compensated a using time-delay algorithm through reaction wheels. The simulation results show that the multi-objective optimal trajectory planning method can reveal the relationships among flight time, fuel consumption, planar view angle and velocity impulse number. This method can provide a series of optimal trajectory according to a number of special tasks. The coordinated control scheme can significantly save thruster fuel for tracking the optimal trajectory, restrain the attitude interferential torque produced by space tether and maintain the relative attitude stability of the operation robot.

  1. Optimization of ammonia fiber expansion (AFEX) pretreatment and enzymatic hydrolysis of Miscanthus x giganteus to fermentable sugars.

    Science.gov (United States)

    Murnen, Hannah K; Balan, Venkatesh; Chundawat, Shishir P S; Bals, Bryan; Sousa, Leonardo da Costa; Dale, Bruce E

    2007-01-01

    Miscanthus x giganteus is a tall perennial grass whose suitability as an energy crop is presently being appraised. There is very little information on the effect of pretreatment and enzymatic saccharification of Miscanthus to produce fermentable sugars. This paper reports sugar yields during enzymatic hydrolysis from ammonia fiber expansion (AFEX) pretreated Miscanthus. Pretreatment conditions including temperature, moisture, ammonia loading, residence time, and enzyme loadings are varied to maximize hydrolysis yields. In addition, further treatments such as soaking the biomass prior to AFEX as well as washing the pretreated material were also attempted to improve sugar yields. The optimal AFEX conditions determined were 160 degrees C, 2:1 (w/w) ammonia to biomass loading, 233% moisture (dry weight basis), and 5 min reaction time for water-soaked Miscanthus. Approximately 96% glucan and 81% xylan conversions were achieved after 168 h enzymatic hydrolysis at 1% glucan loading using 15 FPU/(g of glucan) of cellulase and 64 p-NPGU/(g of glucan) of beta-glucosidase along with xylanase and tween-80 supplementation. A mass balance for the AFEX pretreatment and enzymatic hydrolysis process is presented.

  2. Optimal motion planning of an underactuated spacecraft using wavelet approximate method

    Institute of Scientific and Technical Information of China (English)

    GE Xinsheng; CHEN Liqun; LIU Yanzhu

    2006-01-01

    An optimal motion planning scheme using wavelet approximation is proposed for an underactuated spacecraft. The motion planning of an underactuated spacecraft can be formulated as an optimal control of a drift-free system. A cost functional is used to incorporate the control energy and the final state errors. The motion planning is to determine control inputs to minimize the cost functional.Using the method of wavelet, one can transform an infinite-dimensional optimal control problem to a finite-dimensional one and use GaussNewton algorithm to solve it for a feasible trajectory which satisfies nonholonomic constraints. The proposed scheme has been applied to a rigid spacecraft with two momentum wheels. The numerical simulation results indicate that optimal control with wavelet approximation is an effective approach to steering an underactuated spacecraft system from the initial configuration to the final configuration.

  3. Direct leaf trajectory optimization for volumetric modulated arc therapy planning with sliding window delivery

    CERN Document Server

    Papp, Dávid

    2013-01-01

    We propose a novel optimization model for volumetric modulated arc therapy (VMAT) planning that directly optimizes deliverable leaf trajectories in the treatment plan optimization problem, and eliminates the need for a separate arc-sequencing step. In this model, a 360-degree arc is divided into a given number of arc segments in which the leaves move unidirectionally. This facilitates an algorithm that determines the optimal piecewise linear leaf trajectories for each arc segment, which are deliverable in a given treatment time. Multi-leaf collimator (MLC) constraints, including maximum leaf speed and interdigitation, are accounted for explicitly. The algorithm is customized to allow for VMAT delivery using constant gantry speed and dose rate, however, the algorithm generalizes to variable gantry speed if beneficial. We demonstrate the method for three different tumor sites: a head-and-neck case, a prostate case, and a paraspinal case. For that purpose, we first obtain a reference plan for intensity modulated...

  4. A Graphical Exposition of the Inconsistency of Optimal Monetary Plans

    Science.gov (United States)

    Steindl, Frank G.

    2007-01-01

    The author presents a geometrical framework in which the inability of discretionary policy (consistent policy in the sense of Kydland and Prescott) to be socially optimal is demonstrated. Policy based on a rule results in a higher level of utility. The author extends the model to demonstrate that policy of a Rogoff conservative central banker…

  5. Generating Optimal Stowage Plans for Container Vessel Bays

    DEFF Research Database (Denmark)

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

    2009-01-01

    Millions of containers are stowed every week with goods worth billions of dollars, but container vessel stowage is an all but ne- glected combinatorial optimization problem. In this paper, we introduce a model for stowing containers in a vessel bay which is the result of prob- ably the longest...

  6. Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

    Science.gov (United States)

    Whitaker, May

    2016-01-01

    Purpose 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. Material and methods 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. Results 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. Conclusions 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. PMID:27504129

  7. 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.

  8. An evolutionary algorithm technique for intelligence, surveillance, and reconnaissance plan optimization

    Science.gov (United States)

    Langton, John T.; Caroli, Joseph A.; Rosenberg, Brad

    2008-04-01

    To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effects-based Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology

  9. 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%).

  10. An optimal antenna motion generation using shortest path planning

    Science.gov (United States)

    Jeon, Moon-Jin; Kwon, Dong-Soo

    2017-03-01

    This paper considers an angular velocity minimization method for a satellite antenna. For high speed transmission of science data, a directional antenna with a two-axis gimbal is generally used. When a satellite passes over a ground station while pointing directly at it, the angular velocity of the satellite antenna can increase rapidly due to the gimbal kinematics. The high angular velocity could exceed the dynamic constraint of the antenna. Furthermore, micro vibration induced by high speed antenna rotation during an imaging operation might cause jitter, which can degrade the satellite image quality. To solve this problem, a minimum-velocity antenna motion generation method is proposed. Boundaries of the azimuth and elevation angles of the antenna within an effective beam width are derived using antenna geometry. A minimum-velocity azimuth profile and elevation profile within the boundaries are generated sequentially using a shortest path planning method. For fast and correct generation of the shortest path, a new algorithm called a string nailing algorithm is proposed. A numerical simulation shows that the antenna profile generated by the shortest path planning has a much lower angular velocity than the profiles generated by previous methods. The proposed string nailing algorithm also spends much less computation time than a search-based shortest path planning algorithm to generate almost the same antenna profiles.

  11. 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.

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

    Science.gov (United States)

    2015-06-07

    become available: quantum annealing. Quantum annealing is one of the most accessible quantum algorithms for a computer sci- ence audience not versed...in quantum computing because of its close ties to classical optimization algorithms such as simulated annealing. While large-scale universal quantum ...devices designed to run only this type of quantum algorithm . Other types of quan- tum algorithms are known that take on quite a different form, and are

  13. Economic Analysis of Lagrangian and Genetic Algorithm for the Optimal Capacity Planning of Photovoltaic Generation

    Directory of Open Access Journals (Sweden)

    Jeeng-Min Ling

    2015-01-01

    Full Text Available The optimal allocation problem for a stand-alone photovoltaic (SPV generation can be achieved by good compromise between system objective and constraint requirements. The Lagrange technique (LGT is a traditional method to solve such constrained optimization problem. To consider the nonlinear features of reliability constraints evolving from the consideration of different scenarios, including variations of component cost, load profile and installation location, the implementation of SPV generation planning is time-consuming and conventionally implemented by a probability method. Genetic Algorithm (GA has been successfully applied to many optimization problems. For the optimal allocation of photovoltaic and battery devices, the cost function minimization is implemented by GA to attain global optimum with relative computation simplicity. Analytical comparisons between the results from LGT and GA were investigated and the performance of simulation was discussed. Different planning scenarios show that GA performs better than the Lagrange optimization technique.

  14. Three-Dimensional Dose Optimization for Noncoplanar Treatment Planning with Conformal Fields.

    Science.gov (United States)

    Ma, Ying-Chang L.

    1990-01-01

    Recent advances in imaging techniques, especially three dimensional reconstruction of CT images, have made precision tumor localization feasible. These imaging techniques along with developments in computer controlled radiation treatment machines have provided an important thrust in developing better techniques for cancer treatment. This often requires a complex noncoplanar beam arrangements and elaborate treatment planning, which, unfortunately, are time consuming, costly and dependent on operator expertise and experience. A reliable operator-independent dose optimization tool is therefore desirable, especially for 3D treatment planning. In this dissertation, several approaches (linear programming, quadratic programming, and direct search methods) of computer optimization using various criteria including least sire fitting on the 90% isodose to target periphery, dose uniformity, and integral dose are presented. All of these methods are subject to restrictions on the upper limit of the dose to critical organs. In the quadratic programming approach, Kuhn-Tucker theory was employed to convert the quadratic problem into one which permits application of the very powerful, revised simplex method. Several examples are used to analyze the effectiveness of these dose optimization approaches. The studies show that the quadratic programming approach with the criteria of least square fitting and critical organ constraints is superior in efficiency for dose optimization in 3D treatment planning, particularly for cases with a large number of beams. Use of least square fitting allows one to deduce optimized plans for irregularly shaped targets by employing a multi-isocentric technique. Our studies also illustrate the advantages of using irregular conformal fields, optimized beam energy, and noncoplanar beam arrangements in contrast to the conventional treatment which uses a symmetrical rectangular collimator, fixed beam energy, and coplanar beam arrangements. Optimized plans can

  15. Motion Planning for Vibration Reducing of Free-floating Redundant Manipulators Based on Hybrid Optimization Approach

    Institute of Scientific and Technical Information of China (English)

    LIAO Yihuan; LI Daokui; TANG Guojin

    2011-01-01

    This paper is concerned with optimal motion planning for vibration reducing of flee-floating flexible redundant manipulators.Firstly,dynamic model of the system is established based on Lagrange method,and the motion planning model for vibration reducing is proposed.Secondly,a hybrid optimization approach employing Gauss pseudospectral method(GPM) and direct shooting method(DSM),is proposed to solve the motion planning problem.In this approach,the motion planning problem is transformed into a non-linear parameter optimization problem using GPM,and genetic algorithm(GA) is employed to locate the approximate solution.Subsequently,an optimization model is formulated based on DSM,and sequential quadratic programming (SQP) algorithm is used to obtain the accurate solution,with the approximate solution as an initial reference solution.Finally,several numerical simulations are investigated,and the global vibration or residual vibration of flexible link is obviously reduced by the joint trajectory which is obtained by the hybrid optimization approach.The numerical simulation results indicate that the approach is effective and stable to the motion planning problem of vibration reducing.

  16. Optimization of photon beam energy in aperture-based inverse planning.

    Science.gov (United States)

    St-Hilaire, Jason; Sévigny, Caroline; Beaulieu, Frédéric; Gingras, Luc; Tremblay, Daniel; Beaulieu, Luc

    2009-09-03

    Optimal choice of beam energy in radiation therapy is easy in many well-documented cases, but less obvious in some others. Low-energy beams may provide better conformity around the target than their high-energy counterparts due to reduced lateral scatter, but they also contribute to overdosage of peripheral normal tissue. Beam energy was added as an optimization parameter in an automatic aperture-based inverse planning system. We have investigated two sites (prostate and lung), representative of deep-seated and moderately deep-seated tumors. For each case and different numbers of beam incidences, four plans were optimized: 6 MV, 23 MV, and mixed energy plans with one or two energies per incidence. Each plan was scored with a dose-volume cost function. Cost function values, number of segments, monitor units, dose-volume parameters and isodose distributions were compared. For the prostate and lung cases, energy mixing improved plans in terms of cost function values, with a more important reduction for a small number of beam incidences. Use of high energy allows better peripheral tissue sparing, while keeping similar target coverage and sensitive structures avoidance. Low energy contribution to monitor units usually increased with the number of beam incidences. Thus, for deep-seated and moderately deep-seated tumors, energy optimization can produce interesting plans with less peripheral dose and monitor units than for low energy alone.

  17. Evolutionary View Planning for Optimized UAV Terrain Modeling in a Simulated Environment

    Directory of Open Access Journals (Sweden)

    Ronald A. Martin

    2015-12-01

    Full Text Available This work demonstrates the use of genetic algorithms in optimized view planning for 3D reconstruction applications using small unmanned aerial vehicles (UAVs. The quality of UAV site models is currently highly dependent on manual pilot operations or grid-based automation solutions. When applied to 3D structures, these approaches can result in gaps in the total coverage or inconsistency in final model resolution. Genetic algorithms can effectively explore the search space to locate image positions that produce high quality models in terms of coverage and accuracy. A fitness function is defined, and optimization parameters are selected through semi-exhaustive search. A novel simulation environment for evaluating view plans is demonstrated using terrain generation software. The view planning algorithm is tested in two separate simulation cases: a water drainage structure and a reservoir levee, as representative samples of infrastructure monitoring. The optimized flight plan is compared against three alternate flight plans in each case. The optimized view plan is found to yield terrain models with up to 43% greater accuracy than a standard grid flight pattern, while maintaining comparable coverage and completeness.

  18. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy.

    Science.gov (United States)

    Wu, Q Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment.

  19. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Q Jackie [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Thongphiew, Danthai [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Wang, Zhiheng [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Mathayomchan, Boonyanit [Department of Electrical Engineering and Computer Science, Case Western Reserve University Cleveland, OH (United States); Chankong, Vira [Department of Electrical Engineering and Computer Science, Case Western Reserve University Cleveland, OH (United States); Yoo, Sua [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Lee, W Robert [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States); Yin, Fang-Fang [Department of Radiation Oncology, Duke University Medical Center Durham, NC (United States)

    2008-02-07

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment.

  20. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    Science.gov (United States)

    Wu, Q. Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W. Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. Abstract and preliminary data presented at 49th AAPM Annual Meeting, Minneapolis, MN, USA, July 2007.

  1. 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. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies

    Science.gov (United States)

    Guthier, C. V.; Aschenbrenner, K. P.; Müller, R.; Polster, L.; Cormack, R. A.; Hesser, J. W.

    2016-08-01

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  <  0.01). The optimization times were below one second and thus planing can be considered as real-time capable. The novel CS inspired strategy enables real-time ITP for HDR brachytherapy including catheter optimization. The generated plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  2. Real-time inverse high-dose-rate brachytherapy planning with catheter optimization by compressed sensing-inspired optimization strategies.

    Science.gov (United States)

    Guthier, C V; Aschenbrenner, K P; Müller, R; Polster, L; Cormack, R A; Hesser, J W

    2016-08-21

    This paper demonstrates that optimization strategies derived from the field of compressed sensing (CS) improve computational performance in inverse treatment planning (ITP) for high-dose-rate (HDR) brachytherapy. Following an approach applied to low-dose-rate brachytherapy, we developed a reformulation of the ITP problem with the same mathematical structure as standard CS problems. Two greedy methods, derived from hard thresholding and subspace pursuit are presented and their performance is compared to state-of-the-art ITP solvers. Applied to clinical prostate brachytherapy plans speed-up by a factor of 56-350 compared to state-of-the-art methods. Based on a Wilcoxon signed rank-test the novel method statistically significantly decreases the final objective function value (p  plans are either clinically equivalent or show a better performance with respect to dosimetric measures.

  3. SU-E-T-627: Optimal Partial Arcs in VMAT Planning.

    Science.gov (United States)

    Wala, J; Chen, W; Salari, E; Craft, D

    2012-06-01

    To describe a method for producing minimal delivery time partial arc VMAT plans. We begin with the assumption that dose quality is the primary treatment planning goal. Therefore the first step in the partial arc computation is a 180 beam equi-spaced IMRT multi-criteria optimized treatment plan, which serves as an ideal plan, along with a set of user- specified allowable deviations from this plan. This defines a set of target coverage and healthy organ sparing constraints. We then seek a partial arc plan which recovers this ideal plan but is minimal in delivery time. The search for the optimal partial arc which fulfills the hard constraints is done by wrapping a VMAT fluence map optimization/merging/simplification algorithm called VMERGE. The search is performed over all possible partial arcs, with start and end locations discretized to 20 degree increments, and respecting that the gantry cannot pass underneath the couch. This results in 169 partial arcs. For the ones that yield feasible plans, the complete VMERGE algorithm is run, which minimizes the delivery time for that arc. The minimal delivery time plan that fulfills the dosimetric requirements is returned. We apply the method to a lung and liver case. The time savings are as follows: (full arc time, optimal partial arc time): lung (185 s, 94 s), liver (263 s, 165 s). The optimal arc for the lung lesion, a left anterior target, is 140 degrees centered at 50 degrees. The optimal arc for the liver lesion is 160 degrees centered at -90 degrees. By wrapping a fast VMAT optimization/sequencing routine by an exhaustive search over 169 possible partial arcs, we are able to determine the fastest delivery partial arc. The use of partial arcs can significantly shorten delivery time in VMAT delivery. The project described was supported by Award Number R01CA103904 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the ocial views of the National

  4. Optimal Planning and Operation of Hybrid Energy System Supplemented by Storage Devices

    DEFF Research Database (Denmark)

    Javadi, Mohammad Sadegh; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2017-01-01

    This paper presents a two-stage model for optimal planning and operation of a distribution network. Optimal siting and sizing of renewable energy sources (RES) as well as electrical energy storage (EES) systems are considered in the proposed hybrid energy system. In this context, the planning...... problem is considered as a master problem, while there are different sub-problems associated with the short-term operational problem. To properly handle the uncertainties of forecasted load as well as renewable power generations, fair stochastic models are involved in the sub-problems based on historical...

  5. Collision Distance Detection Based on Swept Volume Strategy for Optimal Motion Plan

    Science.gov (United States)

    Huang, Tsai-Jeon

    A swept volume strategy to detect the collision distances between obstacles is presented in this paper for robot motion planning based on optimization technique. The strategy utilizes the recursive quadratic programming optimization method to perform the motion planning problem. This paper is based on segmental swept volume for convenient distance-to-contact calculation. Hermite interpolation is presented to approach the envelope bounding the swept volume. The new method is capable of handling a modestly non-convex swept volume and it has yielded accurate answers in distance calculations. Also, examples would be presented to illustrate and demonstrate this approach in the paper.

  6. 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.

  7. 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

    2015-01-01

    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...... kinds of uncertainty. An integrated optimization approach of procurement, production and distribution costs associated with the supply chain members has been taken into account. A robust optimization scenario-based approach is used to absorb the influence of uncertain parameters and variables....... 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...

  8. Mixed integer programming improves comprehensibility and plan quality in inverse optimization of prostate HDR-brachytherapy

    CERN Document Server

    Gorissen, Bram L; Hoffmann, Aswin L

    2014-01-01

    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 have long solution times. We decrease the solution time of existing linear and quadratic dose-based programming models (LP and QP, respectively) to allow optimizing over potential catheter positions using mixed integer programming. An additional average speed-up of 75% can be obtained by stopping the solver at an early stage, without deterioration of the plan quality. For a fixed catheter configuration, the dwell time optimization model LP solves to optimality in less than 15 seconds, which confirms earlier results. We propose an iterative procedure for QP that allows to prescribe the target dose as an interval, while retaining independence between the solution time and the number of dose calculation points. This iter...

  9. Optimal Planning of Sustainable Buildings: Integration of Life Cycle Assessment and Optimization in a Decision Support System (DSS

    Directory of Open Access Journals (Sweden)

    Fabio Magrassi

    2016-06-01

    Full Text Available Energy efficiency measures in buildings can provide for a significant reduction of greenhouse gas (GHG emissions. A sustainable design and planning of technologies for energy production should be based on economic and environmental criteria. Life Cycle Assessment (LCA is used to quantify the environmental impacts over the whole cycle of life of production plants. Optimization models can support decisions that minimize costs and negative impacts. In this work, a multi-objective decision problem is formalized that takes into account LCA calculations and that minimizes costs and GHG emissions for general buildings. A decision support system (DSS is applied to a real case study in the Northern Italy, highlighting the advantage provided by the installation of renewable energy. Moreover, a comparison among different optimal and non optimal solution was carried out to demonstrate the effectiveness of the proposed DSS.

  10. Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

    Science.gov (United States)

    Englander, Jacob

    2015-01-01

    Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

  11. D-area oil seepage basin bioventing optimization test plan

    Energy Technology Data Exchange (ETDEWEB)

    Berry, C.J.; Radway, J.C.; Alman, D.; Hazen, T.C.

    1998-12-31

    The D Area Oil Seepage Basin (DOSB) was used from 1952 to 1975 for disposal of petroleum-based products (waste oils), general office and cafeteria waste, and apparently some solvents [trichloroethylene (TCE)/tetrachloroethylene (PCE)]. Numerous analytical results have indicated the presence of TCE and its degradation product vinyl chloride in groundwater in and around the unit, and of petroleum hydrocarbons in soils within the unit. The DOSB is slated for additional assessment and perhaps for environmental remediation. In situ bioremediation represents a technology of demonstrated effectiveness in the reclamation of sites contaminated with petroleum hydrocarbons and chlorinated solvents, and has been retained as an alternative for the cleanup of the DOSB. The Savannah River Site is therefore proposing to conduct a field treatability study designed to demonstrate and optimize the effectiveness of in situ microbiological biodegradative processes at the DOSB. The introduction of air and gaseous nutrients via two horizontal injection wells (bioventing) is expected to enhance biodegradation rates of petroleum components and stimulate microbial degradation of chlorinated solvents. The data gathered in this test will allow a determination of the biodegradation rates of contaminants of concern in the soil and groundwater, allow an evaluation of the feasibility of in situ bioremediation of soil and groundwater at the DOSB, and provide data necessary for the functional design criteria for the final remediation system.

  12. D-area oil seepage basin bioventing optimization test plan

    Energy Technology Data Exchange (ETDEWEB)

    Berry, C.J.; Radway, J.C.; Alman, D.; Hazen, T.C.

    1998-12-31

    The D Area Oil Seepage Basin (DOSB) was used from 1952 to 1975 for disposal of petroleum-based products (waste oils), general office and cafeteria waste, and apparently some solvents [trichloroethylene (TCE)/tetrachloroethylene (PCE)]. Numerous analytical results have indicated the presence of TCE and its degradation product vinyl chloride in groundwater in and around the unit, and of petroleum hydrocarbons in soils within the unit. The DOSB is slated for additional assessment and perhaps for environmental remediation. In situ bioremediation represents a technology of demonstrated effectiveness in the reclamation of sites contaminated with petroleum hydrocarbons and chlorinated solvents, and has been retained as an alternative for the cleanup of the DOSB. The Savannah River Site is therefore proposing to conduct a field treatability study designed to demonstrate and optimize the effectiveness of in situ microbiological biodegradative processes at the DOSB. The introduction of air and gaseous nutrients via two horizontal injection wells (bioventing) is expected to enhance biodegradation rates of petroleum components and stimulate microbial degradation of chlorinated solvents. The data gathered in this test will allow a determination of the biodegradation rates of contaminants of concern in the soil and groundwater, allow an evaluation of the feasibility of in situ bioremediation of soil and groundwater at the DOSB, and provide data necessary for the functional design criteria for the final remediation system.

  13. 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.

  14. Developing a Cell-Based Spatial Optimization Model for Land-Use Patterns Planning

    Directory of Open Access Journals (Sweden)

    Chun-Wei Huang

    2014-12-01

    Full Text Available This study developed a cell-based spatial optimization model compatible with the ArcGIS platform, termed Dynamically Dimensioned Search Landscape Optimization Planning model (DDSLOP, for landscape planning. The development of the proposed model was based on the Dynamically Dimensioned Search Algorithm, which can efficiently find an optimal global solution within the massive solution space inherent to multi-dimensional analysis. Therefore, the DDSLOP model can reveal landscape pattern scenarios suited to specific managerial purposes at a cellular level. To evaluate the DDSLOP model, we applied it to a landscape planning initiative that focused on the conservation of three bird species in the National Taiwan University Highland Experimental Farm (NTU-HEF. We compared the proposed model with the Land-Use Pattern Optimization-library (LUPOlib, which was used in the optimization of landscapes at a patch level. The results of the comparison revealed that our fine scale optimization method has better flexibility, and can therefore form landscape structures, which, overall, provides not only better individual habitats for the target species, but also landscape patterns that foster high habitat connectivity, both important aspects of conservation efforts.

  15. Optimal trajectory planning based on Hamiltonian function of a spherical mobile robot

    Institute of Scientific and Technical Information of China (English)

    Chen Ming; Zhan Qiang; Liu Zengbo; Cai Yao

    2008-01-01

    Designed for planetary exploration, a spherical mobile robot BHQ-1 was briefly introduced.The motion model of BHQ-1 was established and quasi-velocities were introduced to simplify some dynamic quantities.Based on the model, the time- and energy-based optimal trajectory of BHQ-1 was planned with Hamiltonian function.The effects of three key coefficients on the shape and direction of the planned trajectory were discussed by simulations.Experimental result of the robot ability in avoiding an obstacle was presented to validate the trajectory planning method.

  16. Optimization of culture conditions for the expansion of umbilical cord-derived mesenchymal stem or stromal cell-like cells using xeno-free culture conditions.

    Science.gov (United States)

    Hatlapatka, Tim; Moretti, Pierre; Lavrentieva, Antonina; Hass, Ralf; Marquardt, Nicole; Jacobs, Roland; Kasper, Cornelia

    2011-04-01

    First isolated from bone marrow, mesenchymal stem or stromal cells (MSC) were shown to be present in several postnatal and extraembryonic tissues as well as in a large variety of fetal tissues (e.g., fatty tissue, dental pulp, placenta, umbilical cord blood, and tissue). In this study, an optimized protocol for the expansion of MSC-like cells from whole umbilical cord tissue under xeno-free culture conditions is proposed. Different fetal calf sera and human serum (HS) were compared with regard to cell proliferation and MSC marker stability in long-term expansion experiments, and HS was shown to support optimal growth conditions. Additionally, the optimal concentration of HS during the cultivation was determined. With regard to cell proliferative potential, apoptosis, colony-forming unit fibroblast frequency, and cell senescence, our findings suggest that an efficient expansion of the cells is carried out best in media supplemented with 10% HS. Under our given xeno-free culture conditions, MSC-like cells were found to display in vitro immunoprivileged and immunomodulatory properties, which were assessed by co-culture and transwell culture experiments with carboxyfluorescein diacetate succinimidyl ester-labeled peripheral blood mononuclear cells. These findings may be of great value for the establishment of biotechnological protocols for the delivery of sufficient cell numbers of high quality for regenerative medicine purposes.

  17. Guaranteed epsilon-optimal treatment plans with minimum number of beams for stereotactic body radiation therapy

    CERN Document Server

    Yarmand, Hamed

    2013-01-01

    Stereotactic body radiotherapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam's-eye-view) known as "apertures". Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan since the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used simultaneously, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined m...

  18. 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.

  19. 75 FR 27341 - Increasing Market and Planning Efficiency Through Improved Software; Notice of Technical...

    Science.gov (United States)

    2010-05-14

    ..., demand resources (DR, DG, and storage), electric vehicles, dispatchable transmission, and combined cycle... include planning under uncertainty, optimal selection of transmission investments among alternatives, modeling generation expansions in transmission planning models, market- based investment models,...

  20. On the Optimal Degree Of Funding Of Public Sector Pension Plans

    OpenAIRE

    Meijdam, A.C.; Ponds, E.H.M.

    2013-01-01

    Abstract: This paper explores the optimal degree of funding of public sector pension plans. It is assumed that a benevolent social planner decides on the contribution of current taxpayers to the funding of public sector pensions next period, weighing the interests of current and future tax payers. Two elements play a role in the optimal funding decision: the optimal-portfolio choice (i.e. the tradeoff between the expected excess return and the additional risk of funding vis-à-vis pay-as-you-g...

  1. Risk Based Optimal Inspection and Repair Planning for Ship Structures Subjected to Corrosion Deterioration

    Institute of Scientific and Technical Information of China (English)

    李典庆; 张圣坤; 唐文勇

    2004-01-01

    A framework of risk based inspection and repair planning was presented to optimize for the ship structures subjected to corrosion deterioration. The planning problem was formulated as an optimization problem where the expected lifetime costs were minimized with a constraint on the minimum acceptable reliability index. The safety margins were established for the inspection events, the repair events and the failure events for ship structures. Moreover, the formulae were derived to calculate failure probabilities and repair probabilities. Based on them, a component subjected to corrosion is investigated for illustration of the process of selecting the optimal inspection and repair strategy. Furthermore, some sensitivity studies were provided. The results show that the optimal inspection instants should take place before the reliability index reaches the minimum acceptable reliability index. The optimal target failure probability is 10-3. In addition, a balance can be achieved between the risk cost and total expected inspection and repair costs by means of the risk-based optimal inspection and repair method, which is very effective in selecting the optimal inspection and repair strategy.

  2. 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.

  3. 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...

  4. The Research of Gray Algorithm and Information Entropy in Route Planning Optimization

    Directory of Open Access Journals (Sweden)

    Ke Zhao

    2012-12-01

    Full Text Available In order to solve the Unmanned Aerial Vehicle (UAV 3-d track planning problems, according to UAV flight are subject to different threats, UAV flight track was established optimal decision-making system, and the fuel consumption, radar threats, missile threats, anti-aircraft threats and atmosphere threats are determined as the evaluation index of objective function, and optimal mathematical model of UAV flight track is constructed. Experience evaluation method is often used to Weight calculation, but there is certain subjectivity .Therefore information entropy method is adopted to determine the Weights by the set of track plans. Grey incidence analysis method is applied to deal with the gray correlation information between the various indicators and to solve the model. Finally, the optimal model is used to scheme selection for flight track planning problem with four threat radar points, five missile threat points, six artillery threat points and four climate threat points to the threat point of flight track planning scheme options. And get the flight track with the best overall performance and Minimum Comprehensive cost, the research provides a theoretical basis for further studying the three-dimensional UAV flight track optimization.

  5. 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...

  6. 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.

  7. An Approximate Optimal Relationship in the Sampling Plan with Inspection Errors

    Institute of Scientific and Technical Information of China (English)

    YANG Ji-ping; QIU Wan-hua; Martin NEWBY

    2001-01-01

    The paper presents and proves an approximate optimal relationship between sample size n andacceptance number c in the sampling plans under imperfect inspection which minimize the Bayesian risk. Theconclusion generalizes the result obtained by A. Hald on the assumption that the inspection is perfect.

  8. 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…

  9. 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…

  10. On the Optimal Degree Of Funding Of Public Sector Pension Plans

    NARCIS (Netherlands)

    Meijdam, A.C.; Ponds, E.H.M.

    2013-01-01

    Abstract: This paper explores the optimal degree of funding of public sector pension plans. It is assumed that a benevolent social planner decides on the contribution of current taxpayers to the funding of public sector pensions next period, weighing the interests of current and future tax payers. T

  11. A two-layer optimization model for high-speed railway line planning

    Institute of Scientific and Technical Information of China (English)

    Li WANG; Li-min JIA; Yong QIN; Jie XU; Wen-ring MO

    2011-01-01

    Line planning is the first important strategic element in the railway operation planning process,which will directly affect the successive planning to determine the efficiency of the whole railway system.A two-layer optimization model is proposed within a simulation framework to deal with the high-speed railway (HSR) line planning problem.In the model,the top layer aims at achieving an optimal stop-schedule set with the service frequencies,and is formulated as a nonlinear program,solved by genetic algorithm.The objective of top layer is to minimize the total operation cost and unserved passenger volume.Given a specific stop-schedule,the bottom layer focuses on weighted passenger flow assignment,formulated as a mixed integer program with the objective of maximizing the served passenger volume and minimizing the total travel time for all passengers.The case study on Taiwan HSR shows that the proposed two-layer model is better than the existing techniques.In addition,this model is also illustrated with the Beijing-Shanghai HSR in China.The result shows that the two-layer optimization model can reduce computation complexity and that an optimal set of stop-schedules can always be generated with less calculation time.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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)

  17. Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.

    Science.gov (United States)

    Kok, Kai Yit; Rajendran, Parvathy

    2016-01-01

    The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.

  18. Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning.

    Directory of Open Access Journals (Sweden)

    Kai Yit Kok

    Full Text Available The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.

  19. Three-dimensional Path Planning for Underwater Vehicles Based on an Improved Ant Colony Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    L.Yang

    2015-12-01

    Full Text Available Three-dimensional path planning for underwater vehicles is an important problem that focuses on optimizing the route with consideration of various constraints in a complex underwater environment. In this paper, an improved ant colony optimization (IACO algorithm based on pheromone exclusion is proposed to solve the underwater vehicle 3D path planning problem. The IACO algorithm can balance the tasks of exploration and development in the ant search path, and enable the ants in the search process to explore initially and develop subsequently. Then, the underwater vehicle can find the safe path by connecting the chosen nodes of the 3D mesh while avoiding the threat area. This new approach can overcome common disadvantages of the basic ant colony algorithm, such as falling into local extremum, poor quality, and low accuracy. Experimental comparative results demonstrate that this proposed IACO method is more effective and feasible in underwater vehicle 3D path planning than the basic ACO model.

  20. Hierarchical incremental path planning and situation-dependent optimized dynamic motion planning considering accelerations.

    Science.gov (United States)

    Lai, Xue-Cheng; Ge, Shuzhi Sam; Al Mamun, Abdullah

    2007-12-01

    This paper studies a hierarchical approach for incrementally driving a nonholonomic mobile robot to its destination in unknown environments. The A* algorithm is modified to handle a map containing unknown information. Based on it, optimal (discrete) paths are incrementally generated with a periodically updated map. Next, accelerations in varying velocities are taken into account in predicting the robot pose and the robot trajectory resulting from a motion command. Obstacle constraints are transformed to suitable velocity limits so that the robot can move as fast as possible while avoiding collisions when needed. Then, to trace the discrete path, the system searches for a waypoint-directed optimized motion in a reduced 1-D translation or rotation velocity space. Various situations of navigation are dealt with by using different strategies rather than a single objective function. Extensive simulations and experiments verified the efficacy of the proposed approach.

  1. Comparison of IPSA and HIPO inverse planning optimization algorithms for prostate HDR brachytherapy.

    Science.gov (United States)

    Panettieri, Vanessa; Smith, Ryan L; Mason, Natasha J; Millar, Jeremy L

    2014-11-08

    Publications have reported the benefits of using high-dose-rate brachytherapy (HDRB) for the treatment of prostate cancer, since it provides similar biochemical control as other treatments while showing lowest long-term complications to the organs at risk (OAR). With the inclusion of anatomy-based inverse planning opti- mizers, HDRB has the advantage of potentially allowing dose escalation. Among the algorithms used, the Inverse Planning Simulated Annealing (IPSA) optimizer is widely employed since it provides adequate dose coverage, minimizing dose to the OAR, but it is known to generate large dwell times in particular positions of the catheter. As an alternative, the Hybrid Inverse treatment Planning Optimization (HIPO) algorithm was recently implemented in Oncentra Brachytherapy V. 4.3. The aim of this work was to compare, with the aid of radiobiological models, plans obtained with IPSA and HIPO to assess their use in our clinical practice. Thirty patients were calculated with IPSA and HIPO to achieve our department's clinical constraints. To evaluate their performance, dosimetric data were collected: Prostate PTV D90(%), V100(%), V150(%), and V200(%), Urethra D10(%), Rectum D2cc(%), and conformity indices. Additionally tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated with the BioSuite software. The HIPO optimization was performed firstly with Prostate PTV (HIPOPTV) and then with Urethra as priority 1 (HIPOurethra). Initial optimization constraints were then modified to see the effects on dosimetric parameters, TCPs, and NTCPs. HIPO optimizations could reduce TCPs up to 10%-20% for all PTVs lower than 74 cm3. For the urethra, IPSA and HIPOurethra provided similar NTCPs for the majority of volume sizes, whereas HIPOPTV resulted in large NTCP values. These findings were in agreement with dosimetric values. By increasing the PTV maximum dose constraints for HIPOurethra plans, TCPs were found to be in agreement with

  2. Algorithms for joint optimization of stability and diversity in planning combinatorial libraries of chimeric proteins.

    Science.gov (United States)

    Zheng, Wei; Friedman, Alan M; Bailey-Kellogg, Chris

    2009-08-01

    In engineering protein variants by constructing and screening combinatorial libraries of chimeric proteins, two complementary and competing goals are desired: the new proteins must be similar enough to the evolutionarily-selected wild-type proteins to be stably folded, and they must be different enough to display functional variation. We present here the first method, Staversity, to simultaneously optimize stability and diversity in selecting sets of breakpoint locations for site-directed recombination. Our goal is to uncover all "undominated" breakpoint sets, for which no other breakpoint set is better in both factors. Our first algorithm finds the undominated sets serving as the vertices of the lower envelope of the two-dimensional (stability and diversity) convex hull containing all possible breakpoint sets. Our second algorithm identifies additional breakpoint sets in the concavities that are either undominated or dominated only by undiscovered breakpoint sets within a distance bound computed by the algorithm. Both algorithms are efficient, requiring only time polynomial in the numbers of residues and breakpoints, while characterizing a space defined by an exponential number of possible breakpoint sets. We applied Staversity to identify 2-10 breakpoint plans for different sets of parent proteins taken from the purE family, as well as for parent proteins TEM-1 and PSE-4 from the beta-lactamase family. The average normalized distance between our plans and the lower bound for optimal plans is around 2%. Our plans dominate most (60-90% on average for each parent set) of the plans found by other possible approaches, random sampling or explicit optimization for stability with implicit optimization for diversity. The identified breakpoint sets provide a compact representation of good plans, enabling a protein engineer to understand and account for the trade-offs between two key considerations in combinatorial chimeragenesis.

  3. UAV path planning using artificial potential field method updated by optimal control theory

    Science.gov (United States)

    Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

    2016-04-01

    The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

  4. 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)

  5. 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.

  6. 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...... simultaneously, aiming at integrating the market operation and planning as one unified process in the market environment. Subsequently, reliability assessment is performed to evaluate and reinforce the resultant expansion plan from MOOP. The proposed method has been tested with the IEEE 14-bus system...

  7. A Novel Global Path Planning Method for Mobile Robots Based on Teaching-Learning-Based Optimization

    Directory of Open Access Journals (Sweden)

    Zongsheng Wu

    2016-07-01

    Full Text Available The Teaching-Learning-Based Optimization (TLBO algorithm has been proposed in recent years. It is a new swarm intelligence optimization algorithm simulating the teaching-learning phenomenon of a classroom. In this paper, a novel global path planning method for mobile robots is presented, which is based on an improved TLBO algorithm called Nonlinear Inertia Weighted Teaching-Learning-Based Optimization (NIWTLBO algorithm in our previous work. Firstly, the NIWTLBO algorithm is introduced. Then, a new map model of the path between start-point and goal-point is built by coordinate system transformation. Lastly, utilizing the NIWTLBO algorithm, the objective function of the path is optimized; thus, a global optimal path is obtained. The simulation experiment results show that the proposed method has a faster convergence rate and higher accuracy in searching for the path than the basic TLBO and some other algorithms as well, and it can effectively solve the optimization problem for mobile robot global path planning.

  8. 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

  9. Anterior-to-posterior wave of buccal expansion in suction feeding fishes is critical for optimizing fluid flow velocity profile.

    Science.gov (United States)

    Bishop, Kristin L; Wainwright, Peter C; Holzman, Roi

    2008-11-01

    In fishes that employ suction feeding, coordinating the timing of peak flow velocity with mouth opening is likely to be an important feature of prey capture success because this will allow the highest forces to be exerted on prey items when the jaws are fully extended and the flow field is at its largest. Although it has long been known that kinematics of buccal expansion in feeding fishes are characterized by an anterior-to-posterior wave of expansion, this pattern has not been incorporated in most previous computational models of suction feeding. As a consequence, these models have failed to correctly predict the timing of peak flow velocity, which according to the currently available empirical data should occur around the time of peak gape. In this study, we use a simple fluid dynamic model to demonstrate that the inclusion of an anterior-to-posterior wave of buccal expansion can correctly reproduce the empirically determined flow velocity profile, although only under very constrained conditions, whereas models that do not allow this wave of expansion inevitably predict peak velocity earlier in the strike, when the gape is less than half of its maximum. The conditions that are required to produce a realistic velocity profile are as follows: (i) a relatively long time lag between mouth opening and expansion of the more posterior parts of the mouth, (ii) a short anterior portion of the mouth relative to more posterior sections, and (iii) a pattern of movement that begins slowly and then rapidly accelerates. Greater maximum velocities were generated in simulations without the anterior-to-posterior wave of expansion, suggesting a trade-off between maximizing fluid speed and coordination of peak fluid speed with peak gape.

  10. iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans

    Energy Technology Data Exchange (ETDEWEB)

    Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.; Heijmen, Ben J. M. [Department of Radiation Oncology, Erasmus MC Rotterdam, Groene Hilledijk 301, 3075 EA Rotterdam (Netherlands)

    2012-02-15

    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. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a

  11. Optimized Planning of Power Source Capacity in Microgrid, Considering Combinations of Energy Storage Devices

    Directory of Open Access Journals (Sweden)

    Zifa Liu

    2016-12-01

    Full Text Available Since renewable energy resource is universally accepted as a promising method to solve the global energy problem, optimal planning and utilization of various distributed generators (DG and energy storage (ES devices deserve special concern. ES devices possess various characteristics in power density, energy density, response speed (switching speed and lifetime. Besides, as different load types have various requirements on power supply reliability according to their importance, coordinated planning with consideration of reasonable matching between power source and load can efficiently improve power supply reliability and economic efficiency via a customized power supply and compensation strategy. This paper focuses on optimization of power source capacity in microgrid and a coordinated planning strategy is proposed with integrated consideration of characteristics of DG, ES and load. An index named additional compensation ratio (ACR for balancing economic efficiency and reliability is proposed and considered in the strategy. The objective function which aims to minimize life cycle cost (LCC is established considering economic efficiency, reliability and environmental conservation. The proposed planning strategy and optimizing model is calculated and verified through case study of an autonomy microgrid.

  12. Optimal Trajectory Planning and Linear Velocity Feedback Control of a Flexible Piezoelectric Manipulator for Vibration Suppression

    Directory of Open Access Journals (Sweden)

    Junqiang Lou

    2015-01-01

    Full Text Available Trajectory planning is an effective feed-forward control technology for vibration suppression of flexible manipulators. However, the inherent drawback makes this strategy inefficient when dealing with modeling errors and disturbances. An optimal trajectory planning approach is proposed and applied to a flexible piezoelectric manipulator system in this paper, which is a combination of feed-forward trajectory planning method and feedback control of piezoelectric actuators. Specifically, the joint controller is responsible for the trajectory tracking and gross vibration suppression of the link during motion, while the active controller of actuators is expected to deal with the link vibrations after joint motion. In the procedure of trajectory planning, the joint angle of the link is expressed as a quintic polynomial function. And the sum of the link vibration energy is chosen as the objective function. Then, genetic algorithm is used to determine the optimal trajectory. The effectiveness of the proposed method is validated by simulation and experiments. Both the settling time and peak value of the link vibrations along the optimal trajectory reduce significantly, with the active control of the piezoelectric actuators.

  13. Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm

    Science.gov (United States)

    Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.

    This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).

  14. Efficiency gains for Spinal Radiosurgery using Multi-criteria optimization IMRT guided VMAT planning

    Science.gov (United States)

    Chen, Huixiao; Winey, Brian A; Daartz, Juliane; Oh, Kevin S; Shin, John H; Gierga, David P

    2014-01-01

    Purpose To evaluate plan quality and delivery efficiency gains of Volumetric Modulated Arc Therapy (VMAT) versus a Multi-Criteria Optimization based IMRT (MCO-IMRT) for stereotactic radiosurgery of spinal metastases. Methods and Materials MCO-IMRT plans (RayStation V2.5, RaySearch Laboratories, Stockholm, Sweden) of ten spinal radiosurgery cases using 7–9 beams were developed for clinical delivery, and patients were replanned using VMAT with partial arcs. The prescribed dose was 18 Gy, and target coverage was maximized such that the maximum dose to the planning organ-at-risk volume (PRV) of the spinal cord was 10 or 12 Gy. DVH constraints from the clinically acceptable MCO-IMRT plans were utilized for VMAT optimization. Plan quality and delivery efficiency with and without collimator rotation for MCO-IMRT and VMAT were compared and analyzed based upon DVH, PTV coverage, homogeneity index, conformity number, cord PRV sparing, total MU and delivery time. Results VMAT plans were capable of matching most DVH constraints from the MCO-IMRT plans. The ranges of MUs were 4808–7193 for MCO-IMRT without collimator rotation, 3509–5907 for MCO-IMRT with collimator rotation, 4444–7309 for VMAT without collimator rotation and 3277–5643 for VMAT with collimator of 90 degrees. MU for the VMAT plans were similar to their corresponding MCO-IMRT plans, depending upon the complexity of the target and PRV geometries, but had a larger range. The delivery times of the MCO-IMRT and VMAT plans, both with collimator rotation, were 18.3 ± 2.5 minutes and 14.2 ± 2.0 minutes, respectively (p < 0.05). Conclusion MCO-IMRT and VMAT can create clinically acceptable plans for spinal radiosurgery. The MU for MCO-IMRT and VMAT can be reduced significantly by utilizing a collimator rotation following the orientation of the spinal cord. Plan quality for VMAT is similar to MCO-IMRT, with similar MU for both modalities. Delivery times can be reduced by nominally 25% with VMAT. PMID:25413420

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. Kinodynamic RRT*: Optimal Motion Planning for Systems with Linear Differential Constraints

    CERN Document Server

    Webb, Dustin J

    2012-01-01

    We present Kinodynamic RRT*, an incremental sampling-based approach for asymptotically optimal motion planning for robots with linear differential constraints. Our approach extends RRT*, which was introduced for holonomic robots (Karaman et al. 2011), by using a fixed-final-state-free-final-time controller that exactly and optimally connects any pair of states, where the cost function is expressed as a trade-off between the duration of a trajectory and the expended control effort. Our approach generalizes earlier work on extending RRT* to kinodynamic systems, as it guarantees asymptotic optimality for any system with controllable linear dynamics, in state spaces of any dimension. Our approach can be applied to non-linear dynamics as well by using their first-order Taylor approximations. In addition, we show that for the rich subclass of systems with a nilpotent dynamics matrix, closed-form solutions for optimal trajectories can be derived, which keeps the computational overhead of our algorithm compared to tr...

  20. Optimal administrative scale for planning public services: a social cost model applied to Flemish hospital care.

    Science.gov (United States)

    Blank, Jos L T; van Hulst, Bart

    2015-01-01

    In choosing the scale of public services, such as hospitals, both economic and public administrative considerations play important roles. The scale and the corresponding spatial distribution of public institutions have consequences for social costs, defined as the institutions' operating costs and the users' travel costs (which include the money and time costs). Insight into the relationship between scale and spatial distribution and social costs provides a practical guide for the best possible administrative planning level. This article presents a purely economic model that is suitable for deriving the optimal scale for public services. The model also reveals the corresponding optimal administrative planning level from an economic perspective. We applied this model to hospital care in Flanders for three different types of care. For its application, we examined the social costs of hospital services at different levels of administrative planning. The outcomes show that the social costs of rehabilitation in Flanders with planning at the urban level (38 areas) are 11% higher than those at the provincial level (five provinces). At the regional level (18 areas), the social costs of rehabilitation are virtually equal to those at the provincial level. For radiotherapy, there is a difference of 88% in the social costs between the urban and the provincial level. For general care, there are hardly any cost differences between the three administrative levels. Thus, purely from the perspective of social costs, rehabilitation should preferably be planned at the regional level, general services at the urban level and radiotherapy at the provincial level.

  1. Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming

    Directory of Open Access Journals (Sweden)

    P. C. Roling

    2008-01-01

    Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.

  2. Radiobiological effect based treatment plan optimization with the linear quadratic model

    Energy Technology Data Exchange (ETDEWEB)

    Schell, Stefan; Wilkens, Jan J.; Oelfke, Uwe [German Cancer Research Center, Heidelberg (Germany). Dept. of Medical Physics in Radiation Oncology

    2010-07-01

    As an approach towards more biology-oriented treatment planning for external beam radiation therapy, we present the incorporation of local radiation damage models into three dimensional treatment planning. This allows effect based instead of dose based plan optimization which could potentially better match the biologically relevant tradeoff between target and normal tissues. In particular, our approach facilitates an effective comparison of different fractionation schemes. It is based on the linear quadratic model to describe the biological radiation effect. Effect based optimization was integrated into our inverse treatment planning software KonRad, and we demonstrate the resulting differences between conventional and biological treatment planning. Radiation damage can be analyzed both qualitatively and quantitatively in dependence of the fractionation scheme and tissue specific parameters in a three dimensional voxel based system. As an example the potential advantages as well as the associated risks of hypofractionation for prostate cancer are analyzed and visualized with the help of effective dose volume histograms. Our results suggest a very conservative view regarding alternative fractionation schemes since uncertainties in biological parameters are still too big to make reliable clinical predictions. (orig.)

  3. Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning

    Directory of Open Access Journals (Sweden)

    Biwei Tang

    2016-05-01

    Full Text Available Global path planning is a challenging issue in the filed of mobile robotics due to its complexity and the nature of nondeterministic polynomial-time hard (NP-hard. Particle swarm optimization (PSO has gained increasing popularity in global path planning due to its simplicity and high convergence speed. However, since the basic PSO has difficulties balancing exploration and exploitation, and suffers from stagnation, its efficiency in solving global path planning may be restricted. Aiming at overcoming these drawbacks and solving the global path planning problem efficiently, this paper proposes a hybrid PSO algorithm that hybridizes PSO and differential evolution (DE algorithms. To dynamically adjust the exploration and exploitation abilities of the hybrid PSO, a novel PSO, the nonlinear time-varying PSO (NTVPSO, is proposed for updating the velocities and positions of particles in the hybrid PSO. In an attempt to avoid stagnation, a modified DE, the ranking-based self adaptive DE (RBSADE, is developed to evolve the personal best experience of particles in the hybrid PSO. The proposed algorithm is compared with four state-of-the-art evolutionary algorithms. Simulation results show that the proposed algorithm is highly competitive in terms of path optimality and can be considered as a vital alternative for solving global path planning.

  4. A novel optimal distribution system planning framework implementing distributed generation in a deregulated electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Porkar, S. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran); Groupe de Recherches en Electrotechnique et Electronique de Nancy, GREEN-UHP, Universite Henri Poincare de Nancy I, BP 239, 54506 Vandoeuvre les Nancy Cedex (France); Poure, P. [Laboratoire d' Instrumentation Electronique de Nancy, LIEN, EA 3440, Universite Henri Poincare de Nancy I, BP 239, 54506 Vandoeuvre les Nancy Cedex (France); Abbaspour-Tehrani-fard, A. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran); Saadate, S. [Groupe de Recherches en Electrotechnique et Electronique de Nancy, GREEN-UHP, Universite Henri Poincare de Nancy I, BP 239, 54506 Vandoeuvre les Nancy Cedex (France)

    2010-07-15

    This paper introduces a new framework included mathematical model and a new software package interfacing two powerful softwares (MATLAB and GAMS) for obtaining the optimal distributed generation (DG) capacity sizing and sitting investments with capability to simulate large distribution system planning. The proposed optimization model allows minimizing total system planning costs for DG investment, DG operation and maintenance, purchase of power by the distribution companies (DISCOs) from transmission companies (TRANSCOs) and system power losses. The proposed model provides not only the DG size and site but also the new market price as well. Three different cases depending on system conditions and three different scenarios depending on different planning alternatives and electrical market structures, have been considered. They have allowed validating the economical and electrical benefits of introducing DG by solving the distribution system planning problem and by improving power quality of distribution system. DG installation increases the feeders' lifetime by reducing their loading and adds the benefit of using the existing distribution system for further load growth without the need for feeders upgrading. More, by investing in DG, the DISCO can minimize its total planning cost and reduce its customers' bills. (author)

  5. Multimodal function optimization using minimal representation size clustering and its application to planning multipaths.

    Science.gov (United States)

    Hocaoğlu, C; Sanderson, A C

    1997-01-01

    A novel genetic algorithm (GA) using minimal representation size cluster (MRSC) analysis is designed and implemented for solving multimodal function optimization problems. The problem of multimodal function optimization is framed within a hypothesize-and-test paradigm using minimal representation size (minimal complexity) for species formation and a GA. A multiple-population GA is developed to identify different species. The number of populations, thus the number of different species, is determined by the minimal representation size criterion. Therefore, the proposed algorithm reveals the unknown structure of the multimodal function when a priori knowledge about the function is unknown. The effectiveness of the algorithm is demonstrated on a number of multimodal test functions. The proposed scheme results in a highly parallel algorithm for finding multiple local minima. In this paper, a path-planning algorithm is also developed based on the MRSC_GA algorithm. The algorithm utilizes MRSC_GA for planning paths for mobile robots, piano-mover problems, and N-link manipulators. The MRSC_GA is used for generating multipaths to provide alternative solutions to the path-planning problem. The generation of alternative solutions is especially important for planning paths in dynamic environments. A novel iterative multiresolution path representation is used as a basis for the GA coding. The effectiveness of the algorithm is demonstrated on a number of two-dimensional path-planning problems.

  6. Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

    Science.gov (United States)

    Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

    2009-02-01

    A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended

  7. An exact approach to direct aperture optimization in IMRT treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Men Chunhua [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Romeijn, H Edwin [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Taskin, Z Caner [Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida 32611-6595 (United States); Dempsey, James F [Department of Radiation Oncology, University of Florida, Gainesville, Florida 32610-0385 (United States)

    2007-12-21

    We consider the problem of intensity-modulated radiation therapy (IMRT) treatment planning using direct aperture optimization. While this problem has been relatively well studied in recent years, most approaches employ a heuristic approach to the generation of apertures. In contrast, we use an exact approach that explicitly formulates the fluence map optimization (FMO) problem as a convex optimization problem in terms of all multileaf collimator (MLC) deliverable apertures and their associated intensities. However, the number of deliverable apertures, and therefore the number of decision variables and constraints in the new problem formulation, is typically enormous. To overcome this, we use an iterative approach that employs a subproblem whose optimal solution either provides a suitable aperture to add to a given pool of allowable apertures or concludes that the current solution is optimal. We are able to handle standard consecutiveness, interdigitation and connectedness constraints that may be imposed by the particular MLC system used, as well as jaws-only delivery. Our approach has the additional advantage that it can explicitly account for transmission of dose through the part of an aperture that is blocked by the MLC system, yielding a more precise assessment of the treatment plan than what is possible using a traditional beamlet-based FMO problem. Finally, we develop and test two stopping rules that can be used to identify treatment plans of high clinical quality that are deliverable very efficiently. Tests on clinical head-and-neck cancer cases showed the efficacy of our approach, yielding treatment plans comparable in quality to plans obtained by the traditional method with a reduction of more than 75% in the number of apertures and a reduction of more than 50% in beam-on time, with only a modest increase in computational effort. The results also show that delivery efficiency is very insensitive to the addition of traditional MLC constraints; however, jaws

  8. Fast thermal simulations and temperature optimization for hyperthermia treatment planning, including realistic 3D vessel networks.

    Science.gov (United States)

    Kok, H P; van den Berg, C A T; Bel, A; Crezee, J

    2013-10-01

    Accurate thermal simulations in hyperthermia treatment planning require discrete modeling of large blood vessels. The very long computation time of the finite difference based DIscrete VAsculature model (DIVA) developed for this purpose is impractical for clinical applications. In this work, a fast steady-state thermal solver was developed for simulations with realistic 3D vessel networks. Additionally, an efficient temperature-based optimization method including the thermal effect of discrete vasculature was developed. The steady-state energy balance for vasculature and tissue was described by a linear system, which was solved with an iterative method on the graphical processing unit. Temperature calculations during optimization were performed by superposition of several precomputed temperature distributions, calculated with the developed thermal solver. The thermal solver and optimization were applied to a human anatomy, with the prostate being the target region, heated with the eight waveguide 70 MHz AMC-8 system. Realistic 3D pelvic vasculature was obtained from angiography. Both the arterial and venous vessel networks consisted of 174 segments and 93 endpoints with a diameter of 1.2 mm. Calculation of the steady-state temperature distribution lasted about 3.3 h with the original DIVA model, while the newly developed method took only ≈ 1-1.5 min. Temperature-based optimization with and without taking the vasculature into account showed differences in optimized waveguide power of more than a factor 2 and optimized tumor T90 differed up to ≈ 0.5°C. This shows the necessity to take discrete vasculature into account during optimization. A very fast method was developed for thermal simulations with realistic 3D vessel networks. The short simulation time allows online calculations and makes temperature optimization with realistic vasculature feasible, which is an important step forward in hyperthermia treatment planning.

  9. Radiotherapy Planning Using an Improved Search Strategy in Particle Swarm Optimization

    Science.gov (United States)

    Modiri, Arezoo; Gu, Xuejun; Hagan, Aaron M.; Sawant, Amit

    2016-01-01

    Objective Evolutionary stochastic global optimization algorithms are widely used in large-scale, non-convex problems. However, enhancing the search efficiency and repeatability of these techniques often requires well-customized approaches. This study investigates one such approach. Methods We use particle swarm optimization (PSO) algorithm to solve a 4-dimensional 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 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. Results 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. Conclusion The proposed virtual search approach boosts the swarm search efficiency and, consequently, improves the optimization convergence rate and robustness for PSO. Significance RT planning is a large-scale, non-convex 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. PMID:27362755

  10. Improved VMAT planning for head and neck tumors with an advanced optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Klippel, Norbert; Schmuecking, Michael; Terribilini, Dario; Geretschlaeger, Andreas; Aebersold, Daniel M.; Manser, Peter [Bern University Hospital - Inselspital (Switzerland). Div. of Medical Radiation Physics and Dept. of Radiation Oncology

    2015-07-01

    In this study, the ''Progressive Resolution Optimizer PRO3'' (Varian Medical Systems) is compared to the previous version PRO2'' with respect to its potential to improve dose sparing to the organs at risk (OAR) and dose coverage of the PTV for head and neck cancer patients. Materials and Methods For eight head and neck cancer patients, volumetric modulated arc therapy (VMAT) treatment plans were generated in this study. All cases have 2-3 phases and the total prescribed dose (PD) was 60-72 Gy in the PTV. The study is mainly focused on the phase 1 plans, which all have an identical PD of 54 Gy, and complex PTV structures with an overlap to the parotids. Optimization was performed based on planning objectives for the PTV according to ICRU83, and with minimal dose to spinal cord, and parotids outside PTV. In order to assess the quality of the optimization algorithms, an identical set of constraints was used for both, PRO2 and PRO3. The resulting treatment plans were investigated with respect to dose distribution based on the analysis of the dose volume histograms. Results For the phase 1 plans (PD = 54 Gy) the near maximum dose D{sub 2%} of the spinal cord, could be minimized to 22±5 Gy with PRO3, as compared to 32±12 Gy with PRO2, averaged for all patients. The mean dose to the parotids was also lower in PRO3 plans compared to PRO2, but the differences were less pronounced. A PTV coverage of V{sub 95%} = 97±1% could be reached with PRO3, as compared to 86±5% with PRO2. In clinical routine, these PRO2 plans would require modifications to obtain better PTV coverage at the cost of higher OAR doses. Conclusion A comparison between PRO3 and PRO2 optimization algorithms was performed for eight head and neck cancer patients. In general, the quality of VMAT plans for head and neck patients are improved with PRO3 as compared to PRO2. The dose to OARs can be reduced significantly, especially for the spinal cord. These reductions are achieved

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

    DEFF Research Database (Denmark)

    Clausen, Jens

    2007-01-01

    Efficient public transportation is becoming increasingly vital for modern capitals. DSB S-tog a/s is the major supplier of rail traffic on the infrastructure of the city-rail network in Copenhagen. S-tog has experienced a demand for increasing volume and quality of the transportation offered....... 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....

  12. Optimal staggered-grid finite-difference schemes by combining Taylor-series expansion and sampling approximation for wave equation modeling

    Science.gov (United States)

    Yan, Hongyong; Yang, Lei; Li, Xiang-Yang

    2016-12-01

    High-order staggered-grid finite-difference (SFD) schemes have been universally used to improve the accuracy of wave equation modeling. However, the high-order SFD coefficients on spatial derivatives are usually determined by the Taylor-series expansion (TE) method, which just leads to great accuracy at small wavenumbers for wave equation modeling. Some conventional optimization methods can achieve high accuracy at large wavenumbers, but they hardly guarantee the small numerical dispersion error at small wavenumbers. In this paper, we develop new optimal explicit SFD (ESFD) and implicit SFD (ISFD) schemes for wave equation modeling. We first derive the optimal ESFD and ISFD coefficients for the first-order spatial derivatives by applying the combination of the TE and the sampling approximation to the dispersion relation, and then analyze their numerical accuracy. Finally, we perform elastic wave modeling with the ESFD and ISFD schemes based on the TE method and the optimal method, respectively. When the appropriate number and interval for the sampling points are chosen, these optimal schemes have extremely high accuracy at small wavenumbers, and can also guarantee small numerical dispersion error at large wavenumbers. Numerical accuracy analyses and modeling results demonstrate the optimal ESFD and ISFD schemes can efficiently suppress the numerical dispersion and significantly improve the modeling accuracy compared to the TE-based ESFD and ISFD schemes.

  13. A Monte Carlo Algorithm for Universally Optimal Bayesian Sequence Prediction and Planning

    CERN Document Server

    Di Franco, Anthony

    2010-01-01

    The aim of this work is to address the question of whether we can in principle design rational decision-making agents or artificial intelligences embedded in computable physics such that their decisions are optimal in reasonable mathematical senses. Recent developments in rare event probability estimation, recursive bayesian inference, neural networks, and probabilistic planning are sufficient to explicitly approximate reinforcement learners of the AIXI style with non-trivial model classes (here, the class of resource-bounded Turing machines). Consideration of the effects of resource limitations in a concrete implementation leads to insights about possible architectures for learning systems using optimal decision makers as components.

  14. Antiretroviral therapy program expansion in Zambezia Province, Mozambique: geospatial mapping of community-based and health facility data for integrated health planning.

    Directory of Open Access Journals (Sweden)

    Troy D Moon

    Full Text Available OBJECTIVE: To generate maps reflecting the intersection of community-based Voluntary Counseling and Testing (VCT delivery points with facility-based HIV program demographic information collected at the district level in three districts (Ile, Maganja da Costa and Chinde of Zambézia Province, Mozambique; in order to guide planning decisions about antiretroviral therapy (ART program expansion. METHODS: Program information was harvested from two separate open source databases maintained for community-based VCT and facility-based HIV care and treatment monitoring from October 2011 to September 2012. Maps were created using ArcGIS 10.1. Travel distance by foot within a 10 km radius is generally considered a tolerable distance in Mozambique for purposes of adherence and retention planning. RESULTS: Community-based VCT activities in each of three districts were clustered within geographic proximity to clinics providing ART, within communities with easier transportation access, and/or near the homes of VCT volunteers. Community HIV testing results yielded HIV seropositivity rates in some regions that were incongruent with the Ministry of Health's estimates for the entire district (2-13% vs. 2% in Ile, 2-54% vs. 11.5% in Maganja da Costa, and 23-43% vs. 14.4% in Chinde. All 3 districts revealed gaps in regional disbursement of community-based VCT activities as well as access to clinics offering ART. CONCLUSIONS: Use of geospatial mapping in the context of program planning and monitoring allowed for characterizing the location and size of each district's HIV population. In extremely resource limited and logistically challenging settings, maps are valuable tools for informing evidence-based decisions in planning program expansion, including ART.

  15. Value of information methods for planning and analyzing clinical studies optimize decision making and research planning.

    Science.gov (United States)

    Willan, Andrew R; Goeree, Ron; Boutis, Kathy

    2012-08-01

    The results of two randomized clinical trials (RCTs) demonstrate the clinical effectiveness of alternatives to casting for certain ankle and wrist fractures. We illustrate the use of value of information (VOI) methods for evaluating the evidence provided by these studies with respect to decision making. Using cost-effectiveness data from these studies, the expected value of sample information (EVSI) of a future RCT can be determined. If the EVSI exceeds the cost of the future trial for any sample size, then the current evidence is considered insufficient for decision making and a future trial is considered worthwhile. If, on the other hand, there is no sample size for which the EVSI exceeds the cost, then the evidence is considered sufficient, and no future trial is required. We found that the evidence from the ankle study was insufficient to support the adoption of the removable device and determined the optimal sample size for a future trial. Conversely, the evidence from the wrist study was sufficient to support the adoption of the removable device. VOI methods provide a decision-analytic alternative to the standard hypothesis testing approach for assessing the evidence provided by cost-effectiveness studies and for determining sample sizes for RCTs. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. Optimal trajectory planning and train scheduling for urban rail transit systems

    CERN Document Server

    Wang, Yihui; van den Boom, Ton; De Schutter, Bart

    2016-01-01

    This book contributes to making urban rail transport fast, punctual and energy-efficient –significant factors in the importance of public transportation systems to economic, environmental and social requirements at both municipal and national levels. It proposes new methods for shortening passenger travel times and for reducing energy consumption, addressing two major topics: (1) train trajectory planning: the authors derive a nonlinear model for the operation of trains and present several approaches for calculating optimal and energy-efficient trajectories within a given schedule; and (2) train scheduling: the authors develop a train scheduling model for urban rail systems and optimization approaches with which to balance total passenger travel time with energy efficiency and other costs to the operator. Mixed-integer linear programming and pseudospectral methods are among the new methods proposed for single- and multi-train systems for the solution of the nonlinear trajectory planning problem which involv...

  17. Dynamic path planning for mobile robot based on particle swarm optimization

    Science.gov (United States)

    Wang, Yong; Cai, Feng; Wang, Ying

    2017-08-01

    In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

  18. Comment on genetic and global algorithms for optimization of three-dimensional conformal radiotherapy treatment planning

    Energy Technology Data Exchange (ETDEWEB)

    Vaarkamp, Jaap [Joint Department of Physics, Royal Marsden NHS Trust, Sutton, Surrey (United Kingdom). E-mail: jaap@icr.ac.uk

    2001-06-01

    Full text: I would like to make four comments on three papers by two authors (Wu and Zhu 2000, 2001, Wu et al 2000) on one topic: optimization of 3D conformal radiotherapy treatment planning. In the papers, genetic and global algorithms are proposed for this optimization, and the authors claim to be able to generate better treatment plans than those produced manually and used for patient treatment (Wu and Zhu 2000). However, the data in the papers do not warrant such a conclusion and the work contains such serious methodological flaws that only the opposite can have been true. First, in the papers a few treatment plans for patients with different brain tumours are discussed. Dose volume histograms (DVHs) are presented for the target, sometimes the planning target volume, sometimes the clinical target volume, and the organs at risk (OARs): left and right eye, and thyroid or spinal cord. However, other OARs limit dose more in clinical treatment planning, and it is those OARs to which the planner must direct all effort when optimizing the treatment plan. One such important OAR when treating children is the temporal lobes because the dose to the temporal lobes has been associated with a reduction in IQ points (Fuss et al 2000). Also particularly important when treating children are the hypothalamus and pituitary, because they influence growth and the further hormonal development (Schmiegelow et al 1999, 2000). Furthermore, rather than the eyes themselves, the optic chiasm usually gets more serious attention (Fuss et al 1999) and is considered so important that it is often blocked from the treatment fields during the final fractions, thus compromising dose homogeneity in the target. Finally, irradiating the auditory apparatus can lead to a loss of hearing (Lin et al 2000), and, in particular when one side receives a high dose, every effort is made to at least spare the other side. Hence, it is not surprising to find a treatment plan that is superior in some of the

  19. Planning the expansion of distribution: technical and regulatory considerations; Planejamento da expansao da distribuicao: consideracoes tecnicas e regulatorias

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Afonso Henriques Moreira; Haddad, Jamil; Cruz, Ricardo Alexandre Passos da [Universidade Federal de Itajuba (EXCEN/UNIFEI), MG (Brazil). Centro de Excelencia em Eficiencia Energetica, Recursos Naturais e Energia

    2008-07-01

    The article presents the basis for the new planning of power distribution highlighting the beginning of the public hearing process for the creation of PRODIST: Procedures for Distribution of Electric Power by the ANEEL - National Agency of Electrical Energy.

  20. A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

    Directory of Open Access Journals (Sweden)

    Muhammad Farhan Ausaf

    2015-12-01

    Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

  1. [Impact of optimization algorithms on the intensity map in IMRT treatment planning.].

    Science.gov (United States)

    Shimada, Mari; Nakamura, Mitsuhiro; Miyabe, Yuki; Yamamoto, Tokihiro; Teshima, Teruki; Narita, Yuichiro; Mizowaki, Takashi; Nagata, Yasushi; Hiraoka, Masahiro

    2006-01-01

    In inverse planning of IMRT, optimum intensity maps are generated using an optimization algorithm. In this paper, impacts of two different optimization algorithms on the intensity map in IMRT treatment planning were evaluated. These were from the steepest descent (SD) and simulated annealing (SA) methods. The following five patterns were compared: [1] SD with calculation time of 5 min; [2] SD with the terminal criterion based on cost function; [3] SA with calculation time of 5 min; [4] SA with the terminal criterion; and [5] SA with the terminal criterion using a smoothing filter. Differences of D(95%) for the planning target volume, V(70Gy) for the rectum wall and the bladder wall were up to 0.5, 1.8 and 3.2 %, respectively in all patterns. The dosimetric impact was negligible. In contrast, generated intensity maps were sensitive to the algorithms. Intensity maps generated by SA tended to have much fluctuation due to numerical artifacts compared to those generated by SD. The difference in the profile was over 7 % between the algorithms. The smoothing filter decreased the fluctuation in intensity maps of SA. In conclusion, it is important to understand impacts of optimization algorithms on the intensity map and the dose distribution.

  2. Optimal Constant-Stress Accelerated Degradation Test Plans Using Nonlinear Generalized Wiener Process

    Directory of Open Access Journals (Sweden)

    Zhen Chen

    2016-01-01

    Full Text Available Accelerated degradation test (ADT has been widely used to assess highly reliable products’ lifetime. To conduct an ADT, an appropriate degradation model and test plan should be determined in advance. Although many historical studies have proposed quite a few models, there is still room for improvement. Hence we propose a Nonlinear Generalized Wiener Process (NGWP model with consideration of the effects of stress level, product-to-product variability, and measurement errors for a higher estimation accuracy and a wider range of use. Then under the constraints of sample size, test duration, and test cost, the plans of constant-stress ADT (CSADT with multiple stress levels based on the NGWP are designed by minimizing the asymptotic variance of the reliability estimation of the products under normal operation conditions. An optimization algorithm is developed to determine the optimal stress levels, the number of units allocated to each level, inspection frequency, and measurement times simultaneously. In addition, a comparison based on degradation data of LEDs is made to show better goodness-of-fit of the NGWP than that of other models. Finally, optimal two-level and three-level CSADT plans under various constraints and a detailed sensitivity analysis are demonstrated through examples in this paper.

  3. Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

    Directory of Open Access Journals (Sweden)

    Jianfei Ye

    2015-01-01

    Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

  4. A Marine Spatial Planning Framework for the Optimal Sitting of Marine Renewable Energy Installations

    DEFF Research Database (Denmark)

    Azzelino, A.; Kofoed, Jens Peter; Lanfredi, C.;

    2013-01-01

    In this analysis two Danish case studies are investigated using a spatial planning approach. The first case study concerns the area on the west coast of Denmark that has been elected as test site by the Danish Wave Energy Center (DanWEC), a foundation constituted by local authorities, Aalborg...... University supported by the national wave energy industry. The second case study attains the Danish portion of the western Baltic sea, where many offshore windfarms are already installed and many projects are in construction or in the planning stage. The environmental background for the two areas...... and suggest sound criteria for the optimal siting of these infrastructures. The two case studies, concerning respectively a regional and local scale, offer good examples about how spatial planning has the potential to guide the transition from the single sector management toward the integrated management...

  5. Single versus multichannel applicator in high-dose-rate vaginal brachytherapy optimized by inverse treatment planning.

    Science.gov (United States)

    Bahadur, Yasir A; Constantinescu, Camelia; Hassouna, Ashraf H; Eltaher, Maha M; Ghassal, Noor M; Awad, Nesreen A

    2015-01-01

    To retrospectively compare the potential dosimetric advantages of a multichannel vaginal applicator vs. a single channel one in intracavitary vaginal high-dose-rate (HDR) brachytherapy after hysterectomy, and evaluate the dosimetric advantage of fractional re-planning. We randomly selected 12 patients with endometrial carcinoma, who received adjuvant vaginal cuff HDR brachytherapy using a multichannel applicator. For each brachytherapy fraction, two inverse treatment plans (for central channel and multichannel loadings) were performed and compared. The advantage of fractional re-planning was also investigated. Dose-volume-histogram (DVH) analysis showed limited, but statistically significant difference (p = 0.007) regarding clinical-target-volume dose coverage between single and multichannel approaches. For the organs-at-risk rectum and bladder, the use of multichannel applicator demonstrated a noticeable dose reduction, when compared to single channel, but statistically significant for rectum only (p = 0.0001). For D2cc of rectum, an average fractional dose of 6.1 ± 0.7 Gy resulted for single channel vs. 5.1 ± 0.6 Gy for multichannel. For D2cc of bladder, an average fractional dose of 5 ± 0.9 Gy occurred for single channel vs. 4.9 ± 0.8 Gy for multichannel. The dosimetric benefit of fractional re-planning was demonstrated: DVH analysis showed large, but not statistically significant differences between first fraction plan and fractional re-planning, due to large inter-fraction variations for rectum and bladder positioning and filling. Vaginal HDR brachytherapy using a multichannel vaginal applicator and inverse planning provides dosimetric advantages over single channel cylinder, by reducing the dose to organs at risk without compromising the target volume coverage, but at the expense of an increased vaginal mucosa dose. Due to large inter-fraction dose variations, we recommend individual fraction treatment plan optimization.

  6. Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy.

    Science.gov (United States)

    Yarmand, Hamed; Winey, Brian; Craft, David

    2013-09-07

    Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam's-eye-view) known as 'apertures'. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as 'neighbor cuts', based on the concept of 'adjacent beams'. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

  7. Optimization of observation plan based on the stochastic characteristics of the geodetic network

    Science.gov (United States)

    Pachelski, Wojciech; Postek, Paweł

    2016-06-01

    Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required. A numerical example of a 2-D network is illustrated to view the effectiveness of presented method. The results show decrease of the number of observations by 66% with respect to the not optimized observation plan, which still satisfy the assumed accuracy.

  8. An improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling

    Science.gov (United States)

    Dao, Son Duy; Abhary, Kazem; Marian, Romeo

    2017-01-01

    Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to "learn" from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers.

  9. An improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling

    Science.gov (United States)

    Dao, Son Duy; Abhary, Kazem; Marian, Romeo

    2017-01-01

    Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to "learn" from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers.

  10. A spatial multi-objective optimization model for sustainable urban wastewater system layout planning.

    Science.gov (United States)

    Dong, X; Zeng, S; Chen, J

    2012-01-01

    Design of a sustainable city has changed the traditional centralized urban wastewater system towards a decentralized or clustering one. Note that there is considerable spatial variability of the factors that affect urban drainage performance including urban catchment characteristics. The potential options are numerous for planning the layout of an urban wastewater system, which are associated with different costs and local environmental impacts. There is thus a need to develop an approach to find the optimal spatial layout for collecting, treating, reusing and discharging the municipal wastewater of a city. In this study, a spatial multi-objective optimization model, called Urban wastewateR system Layout model (URL), was developed. It is solved by a genetic algorithm embedding Monte Carlo sampling and a series of graph algorithms. This model was illustrated by a case study in a newly developing urban area in Beijing, China. Five optimized system layouts were recommended to the local municipality for further detailed design.

  11. 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

    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...... problems to shipboard systems where some means of generation and storage are also schedulable. First, the question of whether or how much energy storage to include into the system is addressed. Both the storage power rating in MW and the capacity in MWh are optimized. Then, optimal operating strategy......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...

  12. Optimization of observation plan based on the stochastic characteristics of the geodetic network

    Directory of Open Access Journals (Sweden)

    Pachelski Wojciech

    2016-06-01

    Full Text Available Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required.

  13. A holistic approach towards optimal planning of hybrid renewable energy systems: Combining hydroelectric and wind energy

    Science.gov (United States)

    Dimas, Panagiotis; Bouziotas, Dimitris; Efstratiadis, Andreas; Koutsoyiannis, Demetris

    2014-05-01

    Hydropower with pumped storage is a proven technology with very high efficiency that offers a unique large-scale energy buffer. Energy storage is employed by pumping water upstream to take advantage of the excess of produced energy (e.g. during night) and next retrieving this water to generate hydro-power during demand peaks. Excess energy occurs due to other renewables (wind, solar) whose power fluctuates in an uncontrollable manner. By integrating these with hydroelectric plants with pumped storage facilities we can form autonomous hybrid renewable energy systems. The optimal planning and management thereof requires a holistic approach, where uncertainty is properly represented. In this context, a novel framework is proposed, based on stochastic simulation and optimization. This is tested in an existing hydrosystem of Greece, considering its combined operation with a hypothetical wind power system, for which we seek the optimal design to ensure the most beneficial performance of the overall scheme.

  14. Applying Ant Colony Optimization to the Problem of Cell Planning in Mobile Telephone System Radio Network

    Directory of Open Access Journals (Sweden)

    Osmar Viera Carcache

    2017-03-01

    Full Text Available This paper presents a computational proposal for the solution of the Cell Planning Problem. The importance of this problem in the area of Telecommunications imposes it as a reference in the search for new methods of optimization. Due to the complexity of the problem, this work uses a discrete relaxation and proposes a mathematical model for the application of the Meta-heuristic Ant Colony Optimization (ACO. For the analysis of the results, 5 instances of the problem of different sizes were selected and the Ants System (AS algorithm was applied. The results show that the proposal efficiently explores the search space, finding the optimal solution for each instance with a relatively low computational cost. These results are compared with 3 evolutionary alternatives of international reference that have been applied to the same study instances, showing a significant improvement by our proposal.

  15. A role for biological optimization within the current treatment planning paradigm

    Energy Technology Data Exchange (ETDEWEB)

    Das, Shiva [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2009-10-15

    Purpose: Biological optimization using complication probability models in intensity modulated radiotherapy (IMRT) planning has tremendous potential for reducing radiation-induced toxicity. Nevertheless, biological optimization is almost never clinically utilized, probably because of clinician confidence in, and familiarity with, physical dose-volume constraints. The method proposed here incorporates biological optimization after dose-volume constrained optimization so as to improve the dose distribution without detrimentally affecting the important reductions achieved by dose-volume optimization (DVO). Methods: Following DVO, the clinician/planner first identifies ''fixed points'' on the target and organ-at-risk (OAR) dose-volume histograms. These points represent important DVO plan qualities that are not to be violated within a specified tolerance. Biological optimization then maximally reduces a biological metric (illustrated with equivalent uniform dose (EUD) in this work) while keeping the fixed dose-volume points within tolerance limits, as follows. Incremental fluence adjustments are computed and applied to incrementally reduce the OAR EUDs while approximately maintaining the fixed points. This process of incremental fluence adjustment is iterated until the fixed points exceed tolerance. At this juncture, remedial fluence adjustments are computed and iteratively applied to bring the fixed points back within tolerance, without increasing OAR EUDs. This process of EUD reduction followed by fixed-point correction is repeated until no further EUD reduction is possible. The method is demonstrated in the context of a prostate cancer case and olfactory neuroblastoma case. The efficacy of EUD reduction after DVO is evaluated by comparison to an optimizer with purely biological (EUD) OAR objectives. Results: For both cases, EUD reduction after DVO additionally reduced doses, especially high doses, to normal organs. For the prostate case, bladder

  16. TU-EF-304-02: 4D Optimized Treatment Planning for Actively Scanned Proton Therapy Delivered to Moving Target Volume

    Energy Technology Data Exchange (ETDEWEB)

    Bernatowicz, K; Zhang, Y; Weber, D; Lomax, A [Paul Scherrer Institut, Villigen-psi, Aargau (Switzerland)

    2015-06-15

    Purpose: To develop a 4D treatment optimization approach for Pencil Beam Scanned (PBS) proton therapy that includes breathing variability. Method: PBS proton therapy delivers a pattern of proton pencil beams (PBs), distributed to cover the target volume and optimized such as to achieve a homogenous dose distribution across the target. In this work, this optimization step has been enhanced to include advanced 4D dose calculations of liver tumors based on motion extracted from either 4D-CT (representing a single and averaged respiratory cycle) or 4D-CT(MRI) (including breathing variability). The 4D dose calculation is performed per PB on deforming dose grid, and according to the timestamp of each PB, a displacement due to patient’s motion and a change in radiological depth.Three different treatment fields have been optimized in 3D on the end-exhale phase of a 4D-CT liver data set (3D-opt) and then in 4D using the motion extracted from either 4D-CT or 4D-CT(MRI) using deformable image registration. All plans were calculated directly on the PTV without the use of an ITV. The delivery characteristics of the PSI Gantry 2 have been assumed for all calculations. Results: Dose inhomogeneities (D5-D95) in the CTV for the 3D optimized plans recalculated under conditions of variable motion were increased by on average 19.8% compared to the static case. These differences could be reduced by 4D-CT based 4D optimization to 10.5% and by 4D-CT(MRI) based optimization to only 2.3% of the static value. Liver V25 increased by less than 1% using 4D optimization. Conclusion: 4D optimized PBS treatment plans taking into account breathing variability provide for significantly improved robustness against motion and motion variability than those based on 4D-CT alone, and may negate the need of motion specific target expansions. Swiss National Fund Grant (320030-1493942-1)

  17. Orthogonal expansions based stochastic optimal control of Duffing oscillators%基于正交展开方法的Duffing振子随机最优控制

    Institute of Scientific and Technical Information of China (English)

    彭勇波; 李杰

    2011-01-01

    基于多维Hermite多项式的经典均相混沌展开,考察了Duffing振子随机最优多项式控制的正交展开方法,阐明了多项式系数演化与振子系统反应、最优控制力概率特性之间的联系.系统输入采用Karhunen-Loève展开表现的随机地震动.为降低混求解规模,引入位移-速度范数准则,发展了自适应混沌多项式展开策略.同时,基于Lyapunov稳定条件设计控制器的控制增益参数.数值算例分析表明,受控后系统位移和加速度的均方特征得到改善、振子系统的非线性程度减小,基于混沌多项式展开的最优控制方法能明显降低系统的随机涨落和显著改善系统的非线性反应性态.%An orthogonal expansion of stochastic optimal polynomial control, employing the homogenous chaos decomposition with multidimensional Hermite polynomials of random variable argument, of Duffing oscillators is investigated. It reveals the essential relationship between evolution of polynomial coefficients and probabilistic characteristics of oscillator response and control force. The procedure is demonstrated on a base-driven system whereby the ground motion is modeled as a stochastic process with a specified correlation function and is approximated by its Karhunen-Loeve expansion. An adaptive scheme based on a displacement-velocity norm for stochastic approximation with polynomial chaos bases is proposed towards reducing computational effort, which is applied to the identification of phase orbits of nonlinear oscillators. This approximation is then integrated into the design of an optimal polynomial controller, allowing for the efficient estimation of statistics and probability density functions of quantities of interest. Numerical investigations are carried out employing the polynomial chaos expansion and the Lyapunov asymptotic stability condition based control policy. The results reveal that the performance, as gaged by probabilistic quantities of interest, of

  18. SU-E-T-628: A Cloud Computing Based Multi-Objective Optimization Method for Inverse Treatment Planning.

    Science.gov (United States)

    Na, Y; Suh, T; Xing, L

    2012-06-01

    Multi-objective (MO) plan optimization entails generation of an enormous number of IMRT or VMAT plans constituting the Pareto surface, which presents a computationally challenging task. The purpose of this work is to overcome the hurdle by developing an efficient MO method using emerging cloud computing platform. As a backbone of cloud computing for optimizing inverse treatment planning, Amazon Elastic Compute Cloud with a master node (17.1 GB memory, 2 virtual cores, 420 GB instance storage, 64-bit platform) is used. The master node is able to scale seamlessly a number of working group instances, called workers, based on the user-defined setting account for MO functions in clinical setting. Each worker solved the objective function with an efficient sparse decomposition method. The workers are automatically terminated if there are finished tasks. The optimized plans are archived to the master node to generate the Pareto solution set. Three clinical cases have been planned using the developed MO IMRT and VMAT planning tools to demonstrate the advantages of the proposed method. The target dose coverage and critical structure sparing of plans are comparable obtained using the cloud computing platform are identical to that obtained using desktop PC (Intel Xeon® CPU 2.33GHz, 8GB memory). It is found that the MO planning speeds up the processing of obtaining the Pareto set substantially for both types of plans. The speedup scales approximately linearly with the number of nodes used for computing. With the use of N nodes, the computational time is reduced by the fitting model, 0.2+2.3/N, with r̂2>0.99, on average of the cases making real-time MO planning possible. A cloud computing infrastructure is developed for MO optimization. The algorithm substantially improves the speed of inverse plan optimization. The platform is valuable for both MO planning and future off- or on-line adaptive re-planning. © 2012 American Association of Physicists in Medicine.

  19. Capacity Expansion Modeling for Storage Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Elaine; Stoll, Brady; Mai, Trieu

    2017-04-03

    The Resource Planning Model (RPM) is a capacity expansion model designed for regional power systems and high levels of renewable generation. Recent extensions capture value-stacking for storage technologies, including batteries and concentrating solar power with storage. After estimating per-unit capacity value and curtailment reduction potential, RPM co-optimizes investment decisions and reduced-form dispatch, accounting for planning reserves; energy value, including arbitrage and curtailment reduction; and three types of operating reserves. Multiple technology cost scenarios are analyzed to determine level of deployment in the Western Interconnection under various conditions.

  20. SU-E-T-175: Clinical Evaluations of Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Chi, Y; Li, Y; Tian, Z; Gu, X; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States)

    2015-06-15

    Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine was used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.

  1. Opposed optimal strategies of weighting somatosensory inputs for planning reaching movements toward visual and proprioceptive targets.

    Science.gov (United States)

    Blouin, Jean; Saradjian, Anahid H; Lebar, Nicolas; Guillaume, Alain; Mouchnino, Laurence

    2014-11-01

    Behavioral studies have suggested that the brain uses a visual estimate of the hand to plan reaching movements toward visual targets and somatosensory inputs in the case of somatosensory targets. However, neural correlates for distinct coding of the hand according to the sensory modality of the target have not yet been identified. Here we tested the twofold hypothesis that the somatosensory input from the reaching hand is facilitated and inhibited, respectively, when planning movements toward somatosensory (unseen fingers) or visual targets. The weight of the somatosensory inputs was assessed by measuring the amplitude of the somatosensory evoked potential (SEP) resulting from vibration of the reaching finger during movement planning. The target sensory modality had no significant effect on SEP amplitude. However, Spearman's analyses showed significant correlations between the SEPs and reaching errors. When planning movements toward proprioceptive targets without visual feedback of the reaching hand, participants showing the greater SEPs were those who produced the smaller directional errors. Inversely, participants showing the smaller SEPs when planning movements toward visual targets with visual feedback of the reaching hand were those who produced the smaller directional errors. No significant correlation was found between the SEPs and radial or amplitude errors. Our results indicate that the sensory strategy for planning movements is highly flexible among individuals and also for a given sensory context. Most importantly, they provide neural bases for the suggestion that optimization of movement planning requires the target and the reaching hand to both be represented in the same sensory modality. Copyright © 2014 the American Physiological Society.

  2. Coordinated planning of substation expansion and BESS sizing%变电站扩容和电池储能系统容量配置的协调规划方法

    Institute of Scientific and Technical Information of China (English)

    李振文; 颜伟; 刘伟良; 荀吉辉

    2013-01-01

    A coordinated planning model of substation expansion and battery energy storage system (BESS) sizing is proposed, fully considering the effect of BESS charging and discharging on deferring substation expansion. Based on a typical distribution network and its daily load, the objective of the proposed model is to minimize the power purchase costs and the investment and operation costs of BESS and substation. The charging and discharging characteristics of BESS and the network security constraints are included. Candidate discrete/continuous expansion capacity are both considered. It is a multi-period nonlinear mixed-integer programming problem, containing integer variables especially when discrete expansion capacity is considered, which is converted to a continuous optimization problem with complementarities constraints. The decomposed primal-dual interior point method is used to solve the model iteratively and coordinatively, which is decomposed to several single period optimization problems. The case results show that the proposed method can effectively reduce the investment of grid expansion, and optimize the sizing of BESS.%  充分考虑电池储能系统(BESS)的充放电效益对变电站扩容建设的推迟作用,建立了变电站扩容建设和BESS容量配置的协调规划模型。新模型基于一个含风电场的典型地区配电网络及其日负荷曲线,考虑了购电费用和BESS与变电站扩容的综合投资运行费用目标,同时还考虑了BESS的充放电特点和网络的安全约束。其中对于变电站扩容容量包含给定待选与连续可调两种情况。该模型是一个多时段非线性规划问题,在变电站扩容容量为给定待选的情况下还包含整数变量,需将其转换为含互补约束条件的连续优化问题,再采用原对偶解耦内点法将其解耦为单时段优化问题进行协调迭代求解。算例结果表明该方法可以有效减小电网的扩容投资,并实

  3. Distribution Network Expansion Planning Considering Multiple Active Management Strategies%考虑多种主动管理策略的配电网扩展规划

    Institute of Scientific and Technical Information of China (English)

    邢海军; 程浩忠; 杨镜非; 洪绍云; 杨堤; 王存平

    2016-01-01

    A mixed integer second-order cone programming (SOCP) model for active distribution network (ADN) expansion planning is proposed,which minimizes the total investment and operation cost.Four active management strategies consisting of on load tape changer (OLTC) tap adj ustment,distributed generator (DG) curtailment,load curtailment,and reactive power compensation are considered to cut the planning cost and future operation risks of the planning.The planning model allows alternatives to be considered for active management,new wiring,new substation,substation expansion and DG installation. The distribution network planning (DNP) problem is a mixed integer nonlinear programming problem.What with the active management and uncertainties,the DG integration has made the DNP problem considerably complicated.In order to find a polynomial time computable model,the DNP problem is converted to a SOCP model through power flow equations and constraint relaxation.A modified IEEE 33-bus system and Miranda 54-bus system are used to testify the proposed model.%提出了主动配电网扩展规划的混合整数二阶锥规划模型,该模型以总的投资与运行费用最小为目标函数。文中考虑了4种主动管理措施降低规划方案成本及未来的运行风险,包括有载调压变压器调节、切机、切负荷及无功补偿。规划措施包括主动管理、新建线路、新建变电站、扩建变电站、新建分布式电源。配电网规划是一个混合整数非线性规划问题,再加对各种主动管理措施及未来不确定性的考虑,配电网规划问题求解变得相当复杂。基于配电网潮流方程及约束松弛技术,建立了配电网规划的二阶锥规划模型,并利用改进的IEEE 33节点系统及Miranda 54节点系统进行了算例验证。

  4. Beyond optimality: Multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty

    Science.gov (United States)

    Herman, Jonathan D.; Zeff, Harrison B.; Reed, Patrick M.; Characklis, Gregory W.

    2014-10-01

    While optimality is a foundational mathematical concept in water resources planning and management, "optimal" solutions may be vulnerable to failure if deeply uncertain future conditions deviate from those assumed during optimization. These vulnerabilities may produce severely asymmetric impacts across a region, making it vital to evaluate the robustness of management strategies as well as their impacts for regional stakeholders. In this study, we contribute a multistakeholder many-objective robust decision making (MORDM) framework that blends many-objective search and uncertainty analysis tools to discover key tradeoffs between water supply alternatives and their robustness to deep uncertainties (e.g., population pressures, climate change, and financial risks). The proposed framework is demonstrated for four interconnected water utilities representing major stakeholders in the "Research Triangle" region of North Carolina, U.S. The utilities supply well over one million customers and have the ability to collectively manage drought via transfer agreements and shared infrastructure. We show that water portfolios for this region that compose optimal tradeoffs (i.e., Pareto-approximate solutions) under expected future conditions may suffer significantly degraded performance with only modest changes in deeply uncertain hydrologic and economic factors. We then use the Patient Rule Induction Method (PRIM) to identify which uncertain factors drive the individual and collective vulnerabilities for the four cooperating utilities. Our framework identifies key stakeholder dependencies and robustness tradeoffs associated with cooperative regional planning, which are critical to understanding the tensions between individual versus regional water supply goals. Cooperative demand management was found to be the key factor controlling the robustness of regional water supply planning, dominating other hydroclimatic and economic uncertainties through the 2025 planning horizon. Results

  5. Power system modeling and optimization methods vis-a-vis integrated resource planning (IRP)

    Science.gov (United States)

    Arsali, Mohammad H.

    1998-12-01

    The state-of-the-art restructuring of power industries is changing the fundamental nature of retail electricity business. As a result, the so-called Integrated Resource Planning (IRP) strategies implemented on electric utilities are also undergoing modifications. Such modifications evolve from the imminent considerations to minimize the revenue requirements and maximize electrical system reliability vis-a-vis capacity-additions (viewed as potential investments). IRP modifications also provide service-design bases to meet the customer needs towards profitability. The purpose of this research as deliberated in this dissertation is to propose procedures for optimal IRP intended to expand generation facilities of a power system over a stretched period of time. Relevant topics addressed in this research towards IRP optimization are as follows: (1) Historical prospective and evolutionary aspects of power system production-costing models and optimization techniques; (2) A survey of major U.S. electric utilities adopting IRP under changing socioeconomic environment; (3) A new technique designated as the Segmentation Method for production-costing via IRP optimization; (4) Construction of a fuzzy relational database of a typical electric power utility system for IRP purposes; (5) A genetic algorithm based approach for IRP optimization using the fuzzy relational database.

  6. Voltage profile optimization procedures in daily scheduling and in VAR planning of large scale electric systems

    Energy Technology Data Exchange (ETDEWEB)

    Garzillo, A.; Innorta, M.; Marannino, P.; Mognetti, F., Cova, B.

    1988-09-01

    This paper presents some criteria applied to the optimization of voltage profiles and reactive power generation distribution among various resources in daily scheduling and VAR planning. The mathematical models employed in the representation of the two problems are quite similar in spite of the different objective functions and control variable set. The solution is based upon the implementation of two optimal reactive power flow (ORPF) programs. The first ORPF determines a feasible operating point in daily scheduling application, or the minimum investment installations required by system security in VAR planning application. It utilizes a linear algorithm (gradient protection) suggested by Rosen which has been found to be a favourable alternative to the commonly suited simplex method. The second ORPF determines the minimum losses operating point, in the reactive power dispatch, or the most beneficial installation of reactive compensations in VAR planning. The solution of the economy problems is carried out by the Han-Powell algorithm. It essentially solves a set of quadratic sub-problems. In the adopted procedure, the quadratic sub-problems are solved by exploiting an active constraint strategy in the QUADRI subroutine used as an alternative to the well-known Beale method.

  7. Nonlinear dynamic analysis and optimal trajectory planning of a high-speed macro-micro manipulator

    Science.gov (United States)

    Yang, Yi-ling; Wei, Yan-ding; Lou, Jun-qiang; Fu, Lei; Zhao, Xiao-wei

    2017-09-01

    This paper reports the nonlinear dynamic modeling and the optimal trajectory planning for a flexure-based macro-micro manipulator, which is dedicated to the large-scale and high-speed tasks. In particular, a macro- micro manipulator composed of a servo motor, a rigid arm and a compliant microgripper is focused. Moreover, both flexure hinges and flexible beams are considered. By combining the pseudorigid-body-model method, the assumed mode method and the Lagrange equation, the overall dynamic model is derived. Then, the rigid-flexible-coupling characteristics are analyzed by numerical simulations. After that, the microscopic scale vibration excited by the large-scale motion is reduced through the trajectory planning approach. Especially, a fitness function regards the comprehensive excitation torque of the compliant microgripper is proposed. The reference curve and the interpolation curve using the quintic polynomial trajectories are adopted. Afterwards, an improved genetic algorithm is used to identify the optimal trajectory by minimizing the fitness function. Finally, the numerical simulations and experiments validate the feasibility and the effectiveness of the established dynamic model and the trajectory planning approach. The amplitude of the residual vibration reduces approximately 54.9%, and the settling time decreases 57.1%. Therefore, the operation efficiency and manipulation stability are significantly improved.

  8. Optimization of intensity modulated beams in inverse planning by norm minimization

    Science.gov (United States)

    Ringor, Michael Randall

    There are two general paradigms for treatment planning: forward planning and inverse planning. In forward planning, an initial set of treatment parameter values are refined by trial and error until a desired dose distribution is produced. In inverse planning the problem is to determine the appropriate parameter values directly from the desired dose distribution. In this thesis the inverse planning problem (IPP) is posed mathematically as an inverse problem and as an optimization problem. In the case where scatter and attenuation are ignored (the NS-NA model) the inverse problem reduces to the inversion of the Dual Radon operator; if rotational symmetry is assumed, the problem simplifies to the solution of the Abel integral equation. The inverse solutions exhibit negative components and are therefore nonphysical. By formulating the IPP as a constrained optimization problem, the occurrence of negative components can be eliminated using non-negativity constraints. Additional constraints, such as dose limits, can be easily incorporated. The optimality criteria are based on minimizing the L1 and the L2 norms: the former is formulated as a linear program and the latter is formulated as a quadratic program. The numerical solutions of these mathematical programs are obtained in the NS-NA model and in the case where attenuation and scatter are present (SCAT models). In the case of the symmetric NS-NA model, analytical solutions are found using the variational calculus. Since linear and quadratic programs are convex programs, the solutions are global solutions (but not necessarily unique). Comparisons are made between the L1 and the L2 solutions in both the SCAT and the NS-NA dose models for various phantom geometries. The results indicate that norm minimization is a viable approach in the resolution of the IPP; furthermore, the underlying algorithms are sufficiently fast for use in an interactive environment. On a PC running Window NT 4.0 with 192MB RAM, solving the L1

  9. Optimal planning strategy among various arc arrangements for prostate stereotactic body radiotherapy with volumetric modulated arc therapy technique

    Directory of Open Access Journals (Sweden)

    Kang Sang Won

    2017-03-01

    Full Text Available The aim of this study was to determine the optimal strategy among various arc arrangements in prostate plans of stereotactic body radiotherapy with volumetric modulated arc therapy (SBRT-VMAT.

  10. Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2016-01-01

    Full Text Available This paper proposes a potential odor intensity grid based optimization approach for unmanned aerial vehicle (UAV path planning with particle swarm optimization (PSO technique. Odor intensity is created to color the area in the searching space with highest probability where candidate particles may locate. A potential grid construction operator is designed for standard PSO based on different levels of odor intensity. The potential grid construction operator generates two potential location grids with highest odor intensity. Then the middle point will be seen as the final position in current particle dimension. The global optimum solution will be solved as the average. In addition, solution boundaries of searching space in each particle dimension are restricted based on properties of threats in the flying field to avoid prematurity. Objective function is redesigned by taking minimum direction angle to destination into account and a sampling method is introduced. A paired samples t-test is made and an index called straight line rate (SLR is used to evaluate the length of planned path. Experiments are made with other three heuristic evolutionary algorithms. The results demonstrate that the proposed method is capable of generating higher quality paths efficiently for UAV than any other tested optimization techniques.

  11. Path planning for UAV based on quantum-behaved particle swarm optimization

    Science.gov (United States)

    Fu, Yangguang; Ding, Mingyue; Zhou, Chengping; Cai, Chao; Sun, Yangguang

    2009-10-01

    Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach.

  12. A hybrid particle swarm optimization approach with neural network and set pair analysis for transmission network planning

    Institute of Scientific and Technical Information of China (English)

    刘吉成; 颜苏莉; 乞建勋

    2008-01-01

    Transmission network planning (TNP) is a large-scale, complex, with more non-linear discrete variables and the multi-objective constrained optimization problem. In the optimization process, the line investment, network reliability and the network loss are the main objective of transmission network planning. Combined with set pair analysis (SPA), particle swarm optimization (PSO), neural network (NN), a hybrid particle swarm optimization model was established with neural network and set pair analysis for transmission network planning (HPNS). Firstly, the contact degree of set pair analysis was introduced, the traditional goal set was converted into the collection of the three indicators including the identity degree, difference agree and contrary degree. On this bases, using shi(H), the three objective optimization problem was converted into single objective optimization problem. Secondly, using the fast and efficient search capabilities of PSO, the transmission network planning model based on set pair analysis was optimized. In the process of optimization, by improving the BP neural network constantly training so that the value of the fitness function of PSO becomes smaller in order to obtain the optimization program fitting the three objectives better. Finally, compared HPNS with PSO algorithm and the classic genetic algorithm, HPNS increased about 23% efficiency than THA, raised about 3.7% than PSO and improved about 2.96% than GA.

  13. Improvements of hybrid PV-T solar energy systems using Amlouk-Boubaker optothermal expansivity optimizing abacus sketch

    Energy Technology Data Exchange (ETDEWEB)

    Boubaker, K.; Amlouk, M. [Unite de Physique de Dispositifs a Semiconducteurs-UPDS-Faculte des Sciences de Tunis, Campus Universitaire, 2092 Tunis (Tunisia)

    2010-10-15

    This study is a prelude to the definition of a new synthetic parameter inserted in a 2D abacus. This parameter: the Amlouk-Boubaker optothermal expansivity <{psi}{sub AB}>, is defined, for a given PV-T material, as a thermal diffusivity-to-optical effective absorptivity ratio. This parameter's unit evokes a heat flow velocity inside the material. Consequently, the parameter {psi}{sub AB} could be combined with the already known bandgap energy E{sub g}, in order to establish a 2D abacus. A sketched scheme of the 2D abacus is proposed as a guide for investigation and evaluation of PV-T candidate materials like metal oxides, amorphous silicon, zinc-doped binary compounds, and hydrogenated amorphous carbon. Using this abacus, designers will be able to compare solar energy-related materials on the basis of conjoint optical and thermal efficiency. (author)

  14. New developments in modeling network constraints in techno-economic energy system expansion planning models. An overview of existing models and prospects for future approaches

    Energy Technology Data Exchange (ETDEWEB)

    Schoenfelder, Martin; Esser-Frey, Anke; Fichtner, Wolf [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Chair of Energy Economics; Schick, Michael; Heuveline, Vincent [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Engineering Mathematics and Computing Lab.; Leibfried, Thomas [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Inst. of Electric Energy Systems and High-Voltage Technology

    2012-03-15

    This paper is based on Groschke et al. (Z. Energiewirtsch. 33(1):14-22 2009) and continues the description of new developments in modeling network constraints in techno-economic energy system models with a focus on capacity expansion planning and a long-term time horizon. Based on the presentation of recent and future developments in the German energy system, current challenges in energy system modeling are derived. The following analysis of the state of research reveals a lack of high-precision load flow calculation in current energy system models with a long-term time horizon. Hence, this paper presents an outlook on a new mathematical approach, which already proved as a promising method to meet the challenges identified. (orig.)

  15. A dynamic programming model for optimal planning of aquifer storage and recovery facility operations

    Science.gov (United States)

    Uddameri, V.

    2007-01-01

    Aquifer storage recovery (ASR) is an innovative technology with the potential to augment dwindling water resources in regions experiencing rapid growth and development. Planning and design of ASR systems requires quantifying how much water should be stored and appropriate times for storage and withdrawals within a planning period. A monthly scale planning model has been developed in this study to derive optimal (least cost) long-term policies for operating ASR systems and is solved using a recursive deterministic dynamic programming approach. The outputs of the model include annual costs of operation, the amount of water to be imported each month as well as the schedule for storage and extraction. A case study modeled after a proposed ASR system for Mustang Island and Padre Island service areas of the city of Corpus Christi is used to illustrate the utility of the developed model. The results indicate that for the assumed baseline demands, the ASR system is to be kept operational for a period of 4 months starting from May through August. Model sensitivity analysis indicated that increased seasonal shortages can be met using ASR with little additional costs. For the assumed cost structure, a 16% shortage increased the costs by 1.6%. However, the operation time of ASR increased from 4 to 8 months. The developed dynamic programming model is a useful tool to assess the feasibility of evaluating the use of ASR systems during regional-scale water resources planning endeavors.

  16. Optimization Model and Algorithm Design for Airline Fleet Planning in a Multiairline Competitive Environment

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2015-01-01

    Full Text Available This paper presents a multiobjective mathematical programming model to optimize airline fleet size and structure with consideration of several critical factors severely affecting the fleet planning process. The main purpose of this paper is to reveal how multiairline competitive behaviors impact airline fleet size and structure by enhancing the existing route-based fleet planning model with consideration of the interaction between market share and flight frequency and also by applying the concept of equilibrium optimum to design heuristic algorithm for solving the model. Through case study and comparison, the heuristic algorithm is proved to be effective. By using the algorithm presented in this paper, the fleet operational profit is significantly increased compared with the use of the existing route-based model. Sensitivity analysis suggests that the fleet size and structure are more sensitive to the increase of fare price than to the increase of passenger demand.

  17. A bilevel decomposition technique for the optimal planning of offshore platforms

    Directory of Open Access Journals (Sweden)

    M.C.A. Carvalho

    2006-03-01

    Full Text Available There is a great incentive for developing systematic approaches that effectively identify strategies for planning oilfield complexes. This paper proposes an MILP that relies on a reformulation of the model developed by Tsarbopoulou (UCL M.S. Dissertation, London, 2000. Moreover, a bilevel decomposition technique is applied to the MILP. A master problem determines the assignment of platforms to wells and a planning subproblem calculates the timing for fixed assignments. Furthermore, a heuristic search procedure that relies on the distance between platforms and wells is applied in order to reduce the search region. Results show that the decomposition approach using heuristic generates optimal solutions for instances of up to 500 wells and 25 platforms in 10 discrete time periods that otherwise could not be solved with a full-scale approach. One important feature regarding these instances is that they correspond to problems of real-world dimension.

  18. Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization

    Directory of Open Access Journals (Sweden)

    Ronaldo Pornillosa Parreno Jr

    2015-08-01

    Full Text Available Abstract In this study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with electricity. The algorithm provided adifferent approach in clustering problem which combines conceptual and distance-based clustering algorithmsto analyze potential clusters using spanning tree with the shortest possible edge weight and creating final cluster trees based on the test of inconsistency for the edges. The clustering criteria consists of commonly used distance measure with the addition of household information as basis for the ability to pay ATP value. The combination of these two parameters resulted to a more significant and realistic clusters since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings of households. In addition the implications of varying geographical features were incorporated in the algorithm by using routing index across the locations of the households. This new approach of connecting the households in an area was applied in an actual case study of one village or barangay that was not yet energized. The results of clustering algorithm generated cluster trees which could becomethetheoretical basis for power utilities to plan the initial network arrangement of electrification. Scenario analysis conducted on the two strategies of clustering the households provideddifferent alternatives for the optimization of the cost of electrification. Futhermorethe benefits associated with the two strategies formulated from the two scenarios was evaluated using benefit cost ratio BC to determine which is more economically advantageous. The results of the study showed that clustering algorithm proved to be effective in solving electrification optimization problem and serves its purpose as a planning support tool which can facilitate electrification in rural areas and achieve cost-effectiveness.

  19. Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization

    Energy Technology Data Exchange (ETDEWEB)

    Barragán, A. M., E-mail: ana.barragan@uclouvain.be; Differding, S.; Lee, J. A.; Sterpin, E. [Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200 (Belgium); Janssens, G. [Ion Beam Applications S.A., Louvain-la-Neuve 1348 (Belgium)

    2015-04-15

    Purpose: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. Methods: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTV{sub PET}) was calculated from {sup 18}FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number of fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTV{sub PET} inevitably leads to overdosing, which was compared for both optimization schemes. Results: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTV{sub PET} (worst case) were

  20. Treatment planning, optimization, and beam delivery technqiues for intensity modulated proton therapy

    Science.gov (United States)

    Sengbusch, Evan R.

    Physical properties of proton interactions in matter give them a theoretical advantage over photons in radiation therapy for cancer treatment, but they are seldom used relative to photons. The primary barriers to wider acceptance of proton therapy are the technical feasibility, size, and price of proton therapy systems. Several aspects of the proton therapy landscape are investigated, and new techniques for treatment planning, optimization, and beam delivery are presented. The results of these investigations suggest a means by which proton therapy can be delivered more efficiently, effectively, and to a much larger proportion of eligible patients. An analysis of the existing proton therapy market was performed. Personal interviews with over 30 radiation oncology leaders were conducted with regard to the current and future use of proton therapy. In addition, global proton therapy market projections are presented. The results of these investigations serve as motivation and guidance for the subsequent development of treatment system designs and treatment planning, optimization, and beam delivery methods. A major factor impacting the size and cost of proton treatment systems is the maximum energy of the accelerator. Historically, 250 MeV has been the accepted value, but there is minimal quantitative evidence in the literature that supports this standard. A retrospective study of 100 patients is presented that quantifies the maximum proton kinetic energy requirements for cancer treatment, and the impact of those results with regard to treatment system size, cost, and neutron production is discussed. This study is subsequently expanded to include 100 cranial stereotactic radiosurgery (SRS) patients, and the results are discussed in the context of a proposed dedicated proton SRS treatment system. Finally, novel proton therapy optimization and delivery techniques are presented. Algorithms are developed that optimize treatment plans over beam angle, spot size, spot spacing

  1. Ultra-fast treatment plan optimization for volumetric modulated arc therapy (VMAT)

    CERN Document Server

    Men, Chunhua; Jia, Xun; Jiang, Steve B

    2010-01-01

    Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. We consider a cost function consisting two terms, the first which enforces a desired dose distribution while the second guarantees a smooth dose rate variation between successive gantry angles. At each iteration of the column generation method, a subproblem is first solved to generate one more deliverable MLC aperture which potentially decreases the cost function most effectively. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. The iteration of such an algorithm yields a set of deliverable apertures, as well as dose rates, at all gantry angles. Results: The algorithm was preliminarily tested on five prostate and five head-a...

  2. OPEN: Optimized Path Planning Algorithm with Energy Efficiency and Extending Network - Lifetime in WSN

    Directory of Open Access Journals (Sweden)

    Syed Bilal Hussain Shah

    2017-01-01

    Full Text Available In Wireless Sensors Networks (WSNs, researcher’s main focus is on energy preservation and prolonging network lifetime. More energy resources are required in case of remote applications of WSNs, where some of the nodes die early that shorten the lifetime and decrease the stability of the network. It is mainly caused due to the non-optimal Cluster Heads (CHs selection based on single criterion and uneven distribution of energy. We propose a new clustering protocol for both homogeneous and heterogeneous environments, named as Optimized Path planning algorithm with Energy efficiency and Extending Network lifetime in WSN (OPEN. In the proposed protocol, timer value concept is used for CH selection based on multiple criteria. Simulation results prove that OPEN performs better than the existing protocols in terms of the network lifetime, throughput and stability. The results explicitly explain the cluster head selection of OPEN protocol and efficient solution of uneven energy distribution problem.

  3. Power Grid De-icing Optimal Plan Based on Fractional Sieve Method

    Science.gov (United States)

    Xie, Guangbin; Lin, Meihan; Li, Huaqiang

    2017-05-01

    Aiming at the problem that the reliability of system was reduced and the security risk was increased during the DC de-icing period, a decision-making model based on the fractional sieve method was proposed. This model introduced risk assessment theory, and took into account the comprehensive failure probability model of protection action and ice cover. Considering the de-icing condition, a DC de-icing strategy model, which was with the objective function of minimizing the load of shedding and minimizing the operating risk, was proposed. The objective function was optimized by particle swarm optimization algorithm and fractional sieve method. The simulative results of IEEE30-bus system indicated that the load loss caused by de-icing and the operational risk of the system could be effectively reduced by the proposed model. It provided a reference for power department to make a de-icing plan.

  4. Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management

    DEFF Research Database (Denmark)

    Bartolacci, Michael R.; Mihovska, Albena D.; Ozceylan, Dilek

    2013-01-01

    Natural disasters and emergencies create the need for communication between and among the affected populace and emergency responders as well as other parties such as governmental agencies and aid organizations. Such communications include the dissemination of key information such as evacuation...... the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures...... of the deployment or minimizing overall cost to deploy. This work does not focus on the question of what entity will operate the portable base stations or wireless equipment utilized during a disaster, only the question of optimizing placement for planning and real time management purposes. This work examines...

  5. 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...... of the glycerol-based biorefinery supply chains under uncertainties. This framework presents a multi-layered strategy composed of different steps, and it is strongly based on optimization techniques, detailed economic and environmental assessment, and multi-objective optimization under a stochastic environment....... To maximize the business value, the economic objective is measured by the Net Present Value (NPV), whereas the environmental performance is measured by the estimation of a Single Indicator (SI) through the application of LCA methods. As part of the framework, a stochastic multi-period, multi-product and multi...

  6. Optimization Modeling and Decision Support for Wireless Infrastructure Deployment in Disaster Planning and Management

    DEFF Research Database (Denmark)

    Bartolacci, Michael R.; Mihovska, Albena D.; Ozceylan, Dilek

    2013-01-01

    of the deployment or minimizing overall cost to deploy. This work does not focus on the question of what entity will operate the portable base stations or wireless equipment utilized during a disaster, only the question of optimizing placement for planning and real time management purposes. This work examines......Natural disasters and emergencies create the need for communication between and among the affected populace and emergency responders as well as other parties such as governmental agencies and aid organizations. Such communications include the dissemination of key information such as evacuation...... the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures...

  7. Analysis of Cell Load Coupling for LTE Network Planning and Optimization

    CERN Document Server

    Siomina, Iana

    2012-01-01

    System-centric modeling and analysis are of key significance in planning and optimizing cellular networks. In this paper, we provide a mathematical analysis of performance modeling for LTE networks. The system model characterizes the coupling relation between the cell load factors, taking into account non-uniform traffic demand and interference between the cells with arbitrary network topology. Solving the model enables a network-wide performance evaluation in resource consumption. We develop and prove both sufficient and necessary conditions for the feasibility of the load-coupling system, and provide results related to computational aspects for numerically approaching the solution. The theoretical findings are accompanied with experimental results to instructively illustrate the application in optimizing LTE network configuration.

  8. Optimal Planning Strategy for Large PV/Battery System Based on Long-Term Insolation Forecasting

    Science.gov (United States)

    Yona, Atsushi; Uchida, Kosuke; Senjyu, Tomonobu; Funabashi, Toshihisa

    Photovoltaic (PV) systems are rapidly gaining acceptance as some of the best alternative energy sources. Usually the power output of PV system fluctuates depending on weather conditions. In order to control the fluctuating power output for PV system, it requires control method of energy storage system. This paper proposes an optimization approach to determine the operational planning of power output for PV system with battery energy storage system (BESS). This approach aims to obtain more benefit for electrical power selling and to smooth the fluctuating power output for PV system. The optimization method applies genetic algorithm (GA) considering PV power output forecast error. The forecast error is based on our previous works with the insolation forecasting at one day ahead by using weather reported data, fuzzy theory and neural network(NN). The validity of the proposed method is confirmed by the computer simulations.

  9. Optimization of prostate cancer treatment plans using the adjoint transport method and discrete ordinates codes

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, S.; Henderson, D.L. [Dept. of Medical Physics, Madison, WI (United States); Thomadsen, B.R. [Dept. of Medical Physics and Dept. of Human Oncology, Madison (United States)

    2001-07-01

    Interstitial brachytherapy is a type of radiation in which radioactive sources are implanted directly into cancerous tissue. Determination of dose delivered to tissue by photons emitted from implanted seeds is an important step in the treatment plan process. In this paper we will investigate the use of the discrete ordinates method and the adjoint method to calculate absorbed dose in the regions of interest. MIP (mixed-integer programming) is used to determine the optimal seed distribution that conforms the prescribed dose to the tumor and delivers minimal dose to the sensitive structures. The patient treatment procedure consists of three steps: (1) image acquisition with the transrectal ultrasound (TRUS) and assessing the region of interest, (2) adjoint flux computation with discrete ordinate code for inverse dose calculation, and (3) optimization with the MIP branch-and-bound method.

  10. SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Z; Wang, I; Yao, R; Podgorsak, M [Roswell Park Cancer Institute, Buffalo, NY (United States)

    2015-06-15

    Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans and then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance

  11. Optimization of operational planning for wind/hydro hybrid water supply systems

    Energy Technology Data Exchange (ETDEWEB)

    Vieira, Filipe; Ramos, Helena M. [Department of Civil Engineering, Instituto Superior Tecnico, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

    2009-03-15

    Water supply systems (WSS) frequently present high-energy consumption values, which correspond to the major expenses of these systems. Energy costs are a function of its real consumption and of the variability of the daily energy tariff. This paper presents a model of optimization for the energy efficiency in a water supply system. The system is equipped with a pump station and presents excess of available energy in the gravity branch. First, a water turbine is introduced in the system in order to use this excess of hydraulic available energy. Then, an optimization method to define the pump operation planning along the 24 h of simulation, as well as the analysis of the economic benefits resulting from the profit of wind energy to supply the water pumping, while satisfying the system constraints and population demands, is implemented, in order to minimize the global operational costs. The model, developed in MATLAB, uses linear programming and provides the planning strategy to take in each time step, which will influence the following hours. The simulation period considered is one day, sub-divided in hourly time steps. The rules obtained as output of the optimization procedures are subsequently introduced in a hydraulic simulator (e.g. EPANET), in order to verify the system behaviour along the simulation period. The results are compared with the normal operating mode (i.e. without optimization algorithm) and show that energy cost's savings are achieved dependently of the initial reservoir levels or volume. The insertion of the water turbine also generates significant economical benefits for the water supply system. (author)

  12. Optimized LTE cell planning for multiple user density subareas using meta-heuristic algorithms

    KAUST Repository

    Ghazzai, Hakim

    2014-09-01

    Base station deployment in cellular networks is one of the most fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation 4G-LTE cellular networks using meta heuristic algorithms. In this approach, we aim to satisfy both coverage and cell capacity constraints simultaneously by formulating a practical optimization problem. We start by performing a typical coverage and capacity dimensioning to identify the initial required number of base stations. Afterwards, we implement a Particle Swarm Optimization algorithm or a recently-proposed Grey Wolf Optimizer to find the optimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We have also performed Monte Carlo simulations to study the performance of the proposed scheme and computed the average number of users in outage. Results show that our proposed approach respects in all cases the desired network quality of services even for large-scale dimension problems.

  13. Optimization of beamforming and path planning for UAV-assisted wireless relay networks

    Directory of Open Access Journals (Sweden)

    Ouyang Jian

    2014-04-01

    Full Text Available Recently, unmanned aerial vehicles (UAVs acting as relay platforms have attracted considerable attention due to the advantages of extending coverage and improving connectivity for long-range communications. Specifically, in the scenario where the access point (AP is mobile, a UAV needs to find an efficient path to guarantee the connectivity of the relay link. Motivated by this fact, this paper proposes an optimal design for beamforming (BF and UAV path planning. First of all, we study a dual-hop amplify-and-forward (AF wireless relay network, in which a UAV is used as relay between a mobile AP and a fixed base station (BS. In the network, both of the AP and the BS are equipped with multiple antennas, whereas the UAV has a single antenna. Then, we obtain the output signal-to-noise ratio (SNR of the dual-hop relay network. Based on the criterion of maximizing the output SNR, we develop an optimal design to obtain the solution of the optimal BF weight vector and the UAV heading angle. Next, we derive the closed-form outage probability (OP expression to investigate the performance of the dual-hop relay network conveniently. Finally, computer simulations show that the proposed approach can obtain nearly optimal flying path and OP performance, indicating the effectiveness of the proposed algorithm. Furthermore, we find that increasing the antenna number at the BS or the maximal heading angle can significantly improve the performance of the considered relay network.

  14. Impacts of the Load Models on Optimal Planning of Distributed Generation in Distribution System

    Directory of Open Access Journals (Sweden)

    Aashish Kumar Bohre

    2015-01-01

    Full Text Available The optimal planning (sizing and siting of the distributed generations (DGs by using butterfly-PSO/BF-PSO technique to investigate the impacts of load models is presented in this work. The validity of the evaluated results is confirmed by comparing with well-known Genetic Algorithm (GA and standard or conventional particle swarm optimization (PSO. To exhibit its compatibility in terms of load management, an impact of different load models on the size and location of DG has also been presented in this work. The fitness evolution function explored is the multiobjective function (FMO, which is based on the three significant indexes such as active power loss, reactive power loss, and voltage deviation index. The optimal solution is obtained by minimizing the multiobjective fitness function using BF-PSO, GA, and PSO technique. The comparison of the different optimization techniques is given for the different types of load models such as constant, industrial, residential, and commercial load models. The results clearly show that the BF-PSO technique presents the superior solution in terms of compatibility as well as computation time and efforts both. The algorithm has been carried out with 15-bus radial and 30-bus mesh system.

  15. Optimization combinatorial for expansion of gas distribution networks; Otimizacao combinatoria para expansao de redes de distribuicao de gas

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Wagner Emanoel; Gouvea, Elizabeth Ferreira; Goldbarg, Marco Cesar [Rio Grande do Norte Univ., Natal, RN (Brazil). Dept. de Informatica e Matematica Aplicada]. E-mail: wemano@digi.com.br; beth@dimap.ufrn.br; gold@dimap.ufrn.br

    2003-07-01

    Brazil is in a excellent context for the development of natural gas as energy source. The responsibility of design a network to deliver gas increases with the new investments made every day. However the computer aided design (CAD) technologies for gas network design were poor developed because in EUA and Europe have their gas networks from long time ago, in such that only a little of the potential of computer had been explored for the gas network design. This work studies the use of combinatorial optimization techniques and others techniques from evolutionary computing to find layouts to create and expand a network and make the pipeline optimization looking for costs minimizations and respecting all demands of pressures and flow. (author)

  16. Defining the Optimal Planning Target Volume in Image-Guided Stereotactic Radiosurgery of Brain Metastases: Results of a Randomized Trial

    Energy Technology Data Exchange (ETDEWEB)

    Kirkpatrick, John P., E-mail: john.kirkpatrick@dm.duke.edu [Department of Radiation Oncology, Duke University, Durham, North Carolina (United States); Department of Surgery, Duke University, Durham, North Carolina (United States); Wang, Zhiheng [Department of Radiation Oncology, Duke University, Durham, North Carolina (United States); Sampson, John H. [Department of Radiation Oncology, Duke University, Durham, North Carolina (United States); Department of Surgery, Duke University, Durham, North Carolina (United States); McSherry, Frances; Herndon, James E. [Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina (United States); Allen, Karen J.; Duffy, Eileen [Department of Radiation Oncology, Duke University, Durham, North Carolina (United States); Hoang, Jenny K. [Department of Radiology, Duke University, Durham, North Carolina (United States); Chang, Zheng; Yoo, David S.; Kelsey, Chris R.; Yin, Fang-Fang [Department of Radiation Oncology, Duke University, Durham, North Carolina (United States)

    2015-01-01

    Purpose: To identify an optimal margin about the gross target volume (GTV) for stereotactic radiosurgery (SRS) of brain metastases, minimizing toxicity and local recurrence. Methods and Materials: Adult patients with 1 to 3 brain metastases less than 4 cm in greatest dimension, no previous brain radiation therapy, and Karnofsky performance status (KPS) above 70 were eligible for this institutional review board–approved trial. Individual lesions were randomized to 1- or 3- mm uniform expansion of the GTV defined on contrast-enhanced magnetic resonance imaging (MRI). The resulting planning target volume (PTV) was treated to 24, 18, or 15 Gy marginal dose for maximum PTV diameters less than 2, 2 to 2.9, and 3 to 3.9 cm, respectively, using a linear accelerator–based image-guided system. The primary endpoint was local recurrence (LR). Secondary endpoints included neurocognition Mini-Mental State Examination, Trail Making Test Parts A and B, quality of life (Functional Assessment of Cancer Therapy-Brain), radionecrosis (RN), need for salvage radiation therapy, distant failure (DF) in the brain, and overall survival (OS). Results: Between February 2010 and November 2012, 49 patients with 80 brain metastases were treated. The median age was 61 years, the median KPS was 90, and the predominant histologies were non–small cell lung cancer (25 patients) and melanoma (8). Fifty-five, 19, and 6 lesions were treated to 24, 18, and 15 Gy, respectively. The PTV/GTV ratio, volume receiving 12 Gy or more, and minimum dose to PTV were significantly higher in the 3-mm group (all P<.01), and GTV was similar (P=.76). At a median follow-up time of 32.2 months, 11 patients were alive, with median OS 10.6 months. LR was observed in only 3 lesions (2 in the 1 mm group, P=.51), with 6.7% LR 12 months after SRS. Biopsy-proven RN alone was observed in 6 lesions (5 in the 3-mm group, P=.10). The 12-month DF rate was 45.7%. Three months after SRS, no significant change in

  17. Multi-GPU implementation of a VMAT treatment plan optimization algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun; Jia, Xun, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Jiang, Steve B., E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu [Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States); Peng, Fei [Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 (United States)

    2015-06-15

    then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

  18. Cost-effective river rehabilitation planning: optimizing for morphological benefits at large spatial scales.

    Science.gov (United States)

    Langhans, Simone D; Hermoso, Virgilio; Linke, Simon; Bunn, Stuart E; Possingham, Hugh P

    2014-01-01

    River rehabilitation aims to protect biodiversity or restore key ecosystem services but the success rate is often low. This is seldom because of insufficient funding for rehabilitation works but because trade-offs between costs and ecological benefits of management actions are rarely incorporated in the planning, and because monitoring is often inadequate for managers to learn by doing. In this study, we demonstrate a new approach to plan cost-effective river rehabilitation at large scales. The framework is based on the use of cost functions (relationship between costs of rehabilitation and the expected ecological benefit) to optimize the spatial allocation of rehabilitation actions needed to achieve given rehabilitation goals (in our case established by the Swiss water act). To demonstrate the approach with a simple example, we link costs of the three types of management actions that are most commonly used in Switzerland (culvert removal, widening of one riverside buffer and widening of both riversides) to the improvement in riparian zone quality. We then use Marxan, a widely applied conservation planning software, to identify priority areas to implement these rehabilitation measures in two neighbouring Swiss cantons (Aargau, AG and Zürich, ZH). The best rehabilitation plans identified for the two cantons met all the targets (i.e. restoring different types of morphological deficits with different actions) rehabilitating 80,786 m (AG) and 106,036 m (ZH) of the river network at a total cost of 106.1 Million CHF (AG) and 129.3 Million CH (ZH). The best rehabilitation plan for the canton of AG consisted of more and better connected sub-catchments that were generally less expensive, compared to its neighbouring canton. The framework developed in this study can be used to inform river managers how and where best to spend their rehabilitation budget for a given set of actions, ensures the cost-effective achievement of desired rehabilitation outcomes, and helps

  19. WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

    Energy Technology Data Exchange (ETDEWEB)

    Deasy, J. [Memorial Sloan Kettering Cancer Center, New York, NY (United States)

    2015-06-15

    The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning by the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To un