Decennial plan of expansion 1994-2003

International Nuclear Information System (INIS)

1993-12-01

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

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

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

International Nuclear Information System (INIS)

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

1989-01-01

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

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

International Nuclear Information System (INIS)

Ahmadigorji, Masoud; Amjady, Nima

2014-01-01

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

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.

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

Science.gov (United States)

Vaziri Yazdi Pin, Mohammad

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

Optimal planning of integrated multi-energy systems

DEFF Research Database (Denmark)

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-10-15

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

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)

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-12-15

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

Expansion planning for electrical generating systems

International Nuclear Information System (INIS)

1984-01-01

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

DYNAMIC PROGRAMMING – EFFICIENT TOOL FOR POWER SYSTEM EXPANSION PLANNING

Directory of Open Access Journals (Sweden)

SIMO A.

2015-03-01

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

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

International Nuclear Information System (INIS)

1993-10-01

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

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

Directory of Open Access Journals (Sweden)

Mohammad Taghi Ameli

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1992-05-20

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

Optimized Planning Target Volume for Intact Cervical Cancer

International Nuclear Information System (INIS)

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

2012-01-01

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

Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion

Directory of Open Access Journals (Sweden)

Jing Qiu

2017-07-01

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

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.

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...

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.

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

Energy Technology Data Exchange (ETDEWEB)

Lucio, Joao Carlos Martins

1991-12-31

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

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.

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

DEFF Research Database (Denmark)

Zeng, Qing; Zhang, Baohua; Fang, Jiakun

2017-01-01

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

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

International Nuclear Information System (INIS)

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

1997-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-09-01

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

Regulatory Holidays and Optimal Network Expansion

NARCIS (Netherlands)

Willems, Bert; Zwart, Gijsbert

2016-01-01

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

Leader-Follower Approach to Gas-Electricity Expansion Planning Problem

DEFF Research Database (Denmark)

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

2018-01-01

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

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

International Nuclear Information System (INIS)

2001-01-01

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

Studying medium effects with the optimized δ expansion

International Nuclear Information System (INIS)

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

1995-04-01

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

Studying medium effects with the optimized {delta} expansion

Energy Technology Data Exchange (ETDEWEB)

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

1995-04-01

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

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.

A multi-stage stochastic transmission expansion planning method

International Nuclear Information System (INIS)

Akbari, Tohid; Rahimikian, Ashkan; Kazemi, Ahad

2011-01-01

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

Model of clinker capacity expansion

CSIR Research Space (South Africa)

Stylianides, T

1998-10-01

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

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...

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

Science.gov (United States)

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

2018-02-01

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

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

International Nuclear Information System (INIS)

Sadegheih, A.; Drake, P.R.

2008-01-01

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

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

International Nuclear Information System (INIS)

Martindelcampo, C.; Gonzalezbello, C. R.

2012-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-09-01

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

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

International Nuclear Information System (INIS)

Lee, Hun Gyu; Kim, Young Chang

2010-01-01

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

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

International Nuclear Information System (INIS)

1995-01-01

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

IRP methods for Environmental Impact Statements of utility expansion plans

International Nuclear Information System (INIS)

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

1992-01-01

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

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

International Nuclear Information System (INIS)

Koltsaklis, Nikolaos E.; Georgiadis, Michael C.

2015-01-01

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Simultaneous optimization of sequential IMRT plans

International Nuclear Information System (INIS)

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

2005-01-01

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

Optimal separable bases and series expansions

International Nuclear Information System (INIS)

Poirier, B.

1997-01-01

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

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

International Nuclear Information System (INIS)

Saif, Y.; Almansoori, A.

2016-01-01

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

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

International Nuclear Information System (INIS)

Ismail, I.A.H.

1994-01-01

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

Electric utility resource expansion planning using environmental externalities

International Nuclear Information System (INIS)

Mitchell, D.

1992-01-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Interactively exploring optimized treatment plans

International Nuclear Information System (INIS)

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

2005-01-01

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

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

International Nuclear Information System (INIS)

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

1991-01-01

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

Optimizing reserve expansion for disjunct populations of San Joaquin kit fox

Science.gov (United States)

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

2004-01-01

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

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

International Nuclear Information System (INIS)

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

1989-01-01

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

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...

Automated IMRT planning with regional optimization using planning scripts.

Science.gov (United States)

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

2013-01-07

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Decenal plan of electric energy expansion - 2006-2015

International Nuclear Information System (INIS)

2005-01-01

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

Decenal plan of electric energy expansion - 2006-2015

International Nuclear Information System (INIS)

2006-01-01

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

The reference electricity expansion plan of Guatemala

International Nuclear Information System (INIS)

Santizo, Rodolfo

2002-01-01

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

When does treatment plan optimization require inverse planning?

International Nuclear Information System (INIS)

Sherouse, George W.

1995-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1990-12-31

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

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

Science.gov (United States)

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

2012-11-15

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

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

International Nuclear Information System (INIS)

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

1998-01-01

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

Vector-model-supported approach in prostate plan optimization

International Nuclear Information System (INIS)

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

2017-01-01

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

Vector-model-supported approach in prostate plan optimization

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

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

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.

Planning India's long-term energy shipment infrastructures for electricity and coal

International Nuclear Information System (INIS)

Bowen, Brian H.; Canchi, Devendra; Lalit, Vishal Agarwal; Preckel, Paul V.; Sparrow, F.T.; Irwin, Marty W.

2010-01-01

The Purdue Long-Term Electricity Trading and Capacity Expansion Planning Model simultaneously optimizes both transmission and generation capacity expansions. Most commercial electricity system planning software is limited to only transmission planning. An application of the model to India's national power grid, for 2008-2028, indicates substantial transmission expansion is the cost-effective means of meeting the needs of the nation's growing economy. An electricity demand growth rate of 4% over the 20-year planning horizon requires more than a 50% increase in the Government's forecasted transmission capacity expansion, and 8% demand growth requires more than a six-fold increase in the planned transmission capacity expansion. The model minimizes the long-term expansion costs (operational and capital) for the nation's five existing regional power grids and suggests the need for large increases in load-carrying capability between them. Changes in coal policy affect both the location of new thermal power plants and the optimal pattern inter-regional transmission expansions.

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

Energy Technology Data Exchange (ETDEWEB)

Cerda-Arias, Jose Luis

2012-07-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-09-01

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

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.

Optimized t-expansion method for the Rabi Hamiltonian

International Nuclear Information System (INIS)

Travenec, Igor; Samaj, Ladislav

2011-01-01

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

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.

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

Miura, Hideharu; Ozawa, Shuichi; Nagata, Yasushi

2017-09-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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.

Flight plan optimization

Science.gov (United States)

Dharmaseelan, Anoop; Adistambha, Keyne D.

2015-05-01

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

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.

A Modelling Approach for Integrated Planning of Port Capacity- Trade-Offs in Rotterdam Investment Planning

Directory of Open Access Journals (Sweden)

Sander Dekker

2006-03-01

Full Text Available This paper presents a modelling approach for planning ofport capacity. The approach integrates port commercial andpublic interests. It further incorporates route competition andautonomous demand growth. It is applied to port expansion,which can be considered as a strategy for an individual port todeal with route competition. The basis for solving this planningproblem comprises an analysis of port demand and supply in apartial equilibrium model. With such an approach, the reactionof a single port on the change in a transport network comprisingalternative routes to a hinterland destination can be simulated.To establish the optimal expansion strategy, port expansion iscombined with congestion pricing. This is used for the simultaneousdetermination of 1 optimal expansion size, and 2 investmentrecovery period. The modelling approach will be appliedto Rotterdam port focusing on port expansion by means ofland reclamation. The scenmio of the entry of a new competingroute via the Italian port Gioia Tauro is used to address sometrade-offs in Rotterdam investment planning.

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-11-15

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

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

International Nuclear Information System (INIS)

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

2008-01-01

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

The availability of the step optimization in Monaco planning system

International Nuclear Information System (INIS)

Kim, Dae Sup

2014-01-01

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

Impact of equipment failures and wind correlation on generation expansion planning

DEFF Research Database (Denmark)

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

2014-01-01

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

Grid Transmission Expansion Planning Model Based on Grid Vulnerability

Science.gov (United States)

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

2018-03-01

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

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

Optimal Investment Planning of Bulk Energy Storage Systems

Directory of Open Access Journals (Sweden)

Dina Khastieva

2018-02-01

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

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

DEFF Research Database (Denmark)

Sigmund, Ole; Torquato, S.

1997-01-01

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

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

Science.gov (United States)

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

2010-12-01

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

Optimization design of energy deposition on single expansion ramp nozzle

Science.gov (United States)

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

2017-11-01

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

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

International Nuclear Information System (INIS)

Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar

2016-01-01

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

Endoscopic Approach for Tissue Expansion for Different Cosmetic ...

African Journals Online (AJOL)

Background/Purpose: The use of tissue expanders in plastic and reconstruction surgery is now well established for large defects in adults & children. Tissue expansion is one of the reconstructive surgeon's alternatives in providing optimal tissue replacement when skin shortage is a major problem. Predesigned plan about ...

Conventional treatment planning optimization using simulated annealing

International Nuclear Information System (INIS)

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

1995-01-01

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

Global Optimization for Transport Network Expansion and Signal Setting

OpenAIRE

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

2015-01-01

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

A bi-level integrated generation-transmission planning model incorporating the impacts of demand response by operation simulation

International Nuclear Information System (INIS)

Zhang, Ning; Hu, Zhaoguang; Springer, Cecilia; Li, Yanning; Shen, Bo

2016-01-01

Highlights: • We put forward a novel bi-level integrated power system planning model. • Generation expansion planning and transmission expansion planning are combined. • The effects of two sorts of demand response in reducing peak load are considered. • Operation simulation is conducted to reflect the actual effects of demand response. • The interactions between the two levels can guarantee a reasonably optimal result. - Abstract: If all the resources in power supply side, transmission part, and power demand side are considered together, the optimal expansion scheme from the perspective of the whole system can be achieved. In this paper, generation expansion planning and transmission expansion planning are combined into one model. Moreover, the effects of demand response in reducing peak load are taken into account in the planning model, which can cut back the generation expansion capacity and transmission expansion capacity. Existing approaches to considering demand response for planning tend to overestimate the impacts of demand response on peak load reduction. These approaches usually focus on power reduction at the moment of peak load without considering the situations in which load demand at another moment may unexpectedly become the new peak load due to demand response. These situations are analyzed in this paper. Accordingly, a novel approach to incorporating demand response in a planning model is proposed. A modified unit commitment model with demand response is utilized. The planning model is thereby a bi-level model with interactions between generation-transmission expansion planning and operation simulation to reflect the actual effects of demand response and find the reasonably optimal planning result.

Generation expansion planning of the electrical power system in West Java

International Nuclear Information System (INIS)

Nengah Sudja.

1975-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2004-03-01

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

Decision analysis in the expansion planning of the Mexican Electrical System

International Nuclear Information System (INIS)

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

2007-01-01

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

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

International Nuclear Information System (INIS)

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

1990-01-01

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

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.

Using Optimization to Improve Test Planning

Science.gov (United States)

2017-09-01

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

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.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Computational optimization techniques applied to microgrids planning

DEFF Research Database (Denmark)

Gamarra, Carlos; Guerrero, Josep M.

2015-01-01

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

Optimization of importance factors in inverse planning

International Nuclear Information System (INIS)

Xing, L.

1999-01-01

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

Automatic interactive optimization for volumetric modulated arc therapy planning

International Nuclear Information System (INIS)

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

2015-01-01

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

Anisotropic Margin Expansions in 6 Anatomic Directions for Oropharyngeal Image Guided Radiation Therapy

International Nuclear Information System (INIS)

Yock, Adam D.; Garden, Adam S.; Court, Laurence E.; Beadle, Beth M.; Zhang, Lifei; Dong, Lei

2013-01-01

Purpose: The purpose of this work was to determine the expansions in 6 anatomic directions that produced optimal margins considering nonrigid setup errors and tissue deformation for patients receiving image-guided radiation therapy (IGRT) of the oropharynx. Methods and Materials: For 20 patients who had received IGRT to the head and neck, we deformably registered each patient's daily images acquired with a computed tomography (CT)-on-rails system to his or her planning CT. By use of the resulting vector fields, the positions of volume elements within the clinical target volume (CTV) (target voxels) or within a 1-cm shell surrounding the CTV (normal tissue voxels) on the planning CT were identified on each daily CT. We generated a total of 15,625 margins by dilating the CTV by 1, 2, 3, 4, or 5 mm in the posterior, anterior, lateral, medial, inferior, and superior directions. The optimal margins were those that minimized the relative volume of normal tissue voxels positioned within the margin while satisfying 1 of 4 geometric target coverage criteria and 1 of 3 population criteria. Results: Each pair of geometric target coverage and population criteria resulted in a unique, anisotropic, optimal margin. The optimal margin expansions ranged in magnitude from 1 to 5 mm depending on the anatomic direction of the expansion and on the geometric target coverage and population criteria. Typically, the expansions were largest in the medial direction, were smallest in the lateral direction, and increased with the demand of the criteria. The anisotropic margin resulting from the optimal set of expansions always included less normal tissue than did any isotropic margin that satisfied the same pair of criteria. Conclusions: We demonstrated the potential of anisotropic margins to reduce normal tissue exposure without compromising target coverage in IGRT to the head and neck

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

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

Directory of Open Access Journals (Sweden)

Peng Wang

2018-06-01

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

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

Directory of Open Access Journals (Sweden)

Cheng Wang

2013-09-01

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

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

Science.gov (United States)

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

2016-08-01

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

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

Science.gov (United States)

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

2017-12-01

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

Optimal partial-arcs in VMAT treatment planning

International Nuclear Information System (INIS)

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

2012-01-01

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

Capacity expansion model of wind power generation based on ELCC

Science.gov (United States)

Yuan, Bo; Zong, Jin; Wu, Shengyu

2018-02-01

Capacity expansion is an indispensable prerequisite for power system planning and construction. A reasonable, efficient and accurate capacity expansion model (CEM) is crucial to power system planning. In most current CEMs, the capacity of wind power generation is considered as boundary conditions instead of decision variables, which may lead to curtailment or over construction of flexible resource, especially at a high renewable energy penetration scenario. This paper proposed a wind power generation capacity value(CV) calculation method based on effective load-carrying capability, and a CEM that co-optimizes wind power generation and conventional power sources. Wind power generation is considered as decision variable in this model, and the model can accurately reflect the uncertainty nature of wind power.

Optimization approaches for robot trajectory planning

Directory of Open Access Journals (Sweden)

Carlos Llopis-Albert

2018-03-01

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

Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

Energy Technology Data Exchange (ETDEWEB)

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

2012-09-15

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

Analysis of Radiation Treatment Planning by Dose Calculation and Optimization Algorithm

International Nuclear Information System (INIS)

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

2012-01-01

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

Long term electricity expansion analysis to define energy policies for Mexico

International Nuclear Information System (INIS)

Martin del Campo, C.; Guadarrama, R.; Sanchez, O.; Francois, J. L.; Estrada, G.; Izarra, J.; Perez, A.

2010-10-01

A new multi-criteria decision making process based on regret behavior is described. The name we gave it is position vector of minimum regret. A reference which combines the best values of all the criteria is created and positioned in the center of the coordinates of the n-dimensional space; n being the number of criteria. Every alternative is represented by a vector and the magnitude of the position vector is the minimum distance to the reference. The smaller the magnitude of the position vector, the better the corresponding alternative, given that we are looking for the minimum regret. Different weights can be assigned to the criteria. The position vector of minimum regret was applied to the long term electricity expansion planning for Mexico. The study evaluates four parameters: the total generating cost obtained from the objective function after the WASP-IV optimization, the economic risk associated with fuel prices increases, the diversity of fuels participating in the mix of electricity generation, and the external costs associated with health and environmental impacts. The WASP-IV code was used for finding the optimal expansion plan for the Mexican power generating system over the 2008 to 2030 period, under certain restrictions. We decided to study a base case and four additional expansion cases, which are similar to the base case, but each does not consider a certain candidate technology which uses a particular fuel. The reason of studying these five contrasting cases is to quantify the impact, on the evaluation parameters, when a particular fuel is omitted in the expansion plan, and this is very useful for the definition of energy polices concerning diversification by means of nuclear and other CO 2 free options in the mix. The base case is plan A which considers six candidates for expanding the generation system. Plan B does not consider coal, plan C does not consider oil, plan D excludes nuclear energy, and plan E natural gas. After the decision analysis

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)

Optimizing power system investments and resilience against attacks

International Nuclear Information System (INIS)

Fang, Yiping; Sansavini, Giovanni

2017-01-01

This paper studies the combination of capacity expansion and switch installation in electric systems that ensures optimum performance under nominal operations and attacks. The planner–attacker–defender model is adopted to develop decisions that minimize investment and operating costs, and functionality loss after attacks. The model bridges long-term system planning for transmission expansion and short-term switching operations in reaction to attacks. The mixed-integer optimization is solved by decomposition via two-layer cutting plane algorithm. Numerical results on an IEEE system shows that small investments in transmission line switching enhance resilience by responding to disruptions via system reconfiguration. Sensitivity analyses show that transmission planning under the assumption of small-scale attacks provides the most robust strategy, i.e. the minimum-regret planning, if many constraints and limited investment budget affect the planning. On the other hand, the assumption of large-scale attacks provides the most robust strategy if the planning process involves large flexibility and budget. - Highlights: • Investment optimization in power systems under attacks is presented. • Capacity expansion and switch installation for system reconfiguration are combined. • The problem is solved by decomposition via two-layer cutting plane algorithm. • Small investments in switch installation enhance resilience by response to attacks. • Sensitivity analyses identify robust planning against different attack scenarios.

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...

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)

On the role of modeling parameters in IMRT plan optimization

International Nuclear Information System (INIS)

Krause, Michael; Scherrer, Alexander; Thieke, Christian

2008-01-01

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2006-12-01

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Multi-objective optimization of inverse planning for accurate radiotherapy

International Nuclear Information System (INIS)

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

2011-01-01

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

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

OpenAIRE

Kimms, Alf

1996-01-01

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

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

Treatment planning optimization for linear accelerator radiosurgery

International Nuclear Information System (INIS)

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

1998-01-01

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

A fast optimization algorithm for multicriteria intensity modulated proton therapy planning

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Science.gov (United States)

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

2010-09-01

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

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

Plug pattern optimization for gamma knife radiosurgery treatment planning

International Nuclear Information System (INIS)

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

2003-01-01

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

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

International Nuclear Information System (INIS)

Deufel, Christopher L; Furutani, Keith M

2014-01-01

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

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

Optimal day-ahead operational planning of microgrids

International Nuclear Information System (INIS)

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

2016-01-01

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

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)

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Threshold-driven optimization for reference-based auto-planning

Science.gov (United States)

Long, Troy; Chen, Mingli; Jiang, Steve; Lu, Weiguo

2018-02-01

We study threshold-driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH for IMRT treatment planning. We present a framework for threshold-driven optimization for reference-based auto-planning (TORA). Commonly used voxel-based quadratic penalties have two components for penalizing under- and over-dosing of voxels: a reference dose threshold and associated penalty weight. Conventional manual- and auto-planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and often inconsistent method for planning toward some reference DVH. However, driving a dose distribution by threshold values instead of preference weights can achieve similar plans with less computational effort. The proposed methodology spatially assigns reference DVH information to threshold values, and iteratively improves the quality of that assignment. The methodology effectively handles both sub-optimal and infeasible DVHs. TORA was applied to a prostate case and a liver case as a proof-of-concept. Reference DVHs were generated using a conventional voxel-based objective, then altered to be either infeasible or easy-to-achieve. TORA was able to closely recreate reference DVHs in 5-15 iterations of solving a simple convex sub-problem. TORA has the potential to be effective for auto-planning based on reference DVHs. As dose prediction and knowledge-based planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, efficient way will be crucial for automated planning. A threshold-focused objective tuning should be explored over conventional methods of updating preference weights for DVH-guided treatment planning.

[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.

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

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

Science.gov (United States)

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

2005-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1994-05-01

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

The equivalence of multi-criteria methods for radiotherapy plan optimization

International Nuclear Information System (INIS)

Breedveld, Sebastiaan; Storchi, Pascal R M; Heijmen, Ben J M

2009-01-01

Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2pεc (2-phase ε-constraint) method is based on the ε-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.

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

Directory of Open Access Journals (Sweden)

Jaime A. López-López

2016-07-01

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

Robust Optimization Model for Production Planning Problem under Uncertainty

Directory of Open Access Journals (Sweden)

Pembe GÜÇLÜ

2017-01-01

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

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.

PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Science.gov (United States)

2005-09-01

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

Spatiotemporal radiotherapy planning using a global optimization approach

Science.gov (United States)

Adibi, Ali; Salari, Ehsan

2018-02-01

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

Energy efficiency resource modeling in generation expansion planning

International Nuclear Information System (INIS)

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

2014-01-01

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

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)

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.

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)

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)

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.

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

OpenAIRE

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

2016-01-01

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

Fujian electric system analysis and nuclear power planning

International Nuclear Information System (INIS)

Lin Jianwen; Fu Qiang; Cheng Ping

1994-11-01

The objective of the study is to conduct a long term electric expansion planning and nuclear power planning for Fujian Province. The Wien Automatic System Planning Package (WASP-III) is used to optimize the electric system. Probabilistic Simulation is one of the most favorite techniques for middle and long term generation and production cost planning of electric power system. The load duration curve is obtained by recording the load data of a time interval into a monotone non-increasing sense. Polynomial function is used to describe the load duration curve (LDC), and this LDC is prepared for probabilistic simulation in WASP-III. WASP-III is a dynamic optimizing module in the area of supply modelling. It could find out the economically optimal expansion plan for a power generating system over a period of up to thirty years, with the constraints given by the planners. The optimum is evaluated in terms of minimum discounted total costs. Generating costs, amount of energy not served and reliability of the system are analyzed in the system expansion planning by using the probabilistic simulation method. The following conclusions can be drawn from this study. Hydro electricity is the cheapest one of all available technologies and resources. After the large hydro station is committed at the end of 1995, more base load power plants are needed in the system. Coal-fired power plants with capacity of 600 MWe will be the most competitive power plants in the future of the system. At the end of the studying period, about half of the stalled capacity will be composed of these power plants. Nuclear power plants with capacity of 600 MWe are suitable for the system after the base load increases to a certain level. Oil combustion units will decrease the costs of the system. (12 tabs., 6 figs.)

Energy and nuclear power planning study for Armenia

International Nuclear Information System (INIS)

2004-07-01

The Energy and Nuclear Power Planning (ENPP) study for Armenia has been conducted under the technical cooperation programme of the International Atomic Energy Agency (IAEA). The objective of the study was to analyze the electricity demand as part of the total final energy demand in various scenarios of Armenian socioeconomic and technological development, and to develop economically optimized electric generating system expansion plans for meeting the electric power demand, and to assess the role that nuclear energy could play within these optimal programs. The specific objectives of this study were: to define the role that nuclear power could play in the future electricity supply in Armenia, based on a least-cost expansion planning analysis of the country's power system; to analyze the environmental impacts of such a nuclear power development; to evaluate the financial viability of the envisaged nuclear power development program; to train a group of Armenian experts in the use of the IAEA's energy models

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

International Nuclear Information System (INIS)

Seddighi, Amir Hossein; Ahmadi-Javid, Amir

2015-01-01

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

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.

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

Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion

International Nuclear Information System (INIS)

Martinez, Lauro J.; Lambert, James H.; Karvetski, Christopher W.

2011-01-01

Planning the expansion and energy security of electricity capacity for a national electricity utility is a complex task in almost any economy. Planning is usually an iterative activity and can involve the use of large scale planning optimization systems accompanied by assessment of uncertain scenarios emerging from economic, technological, environmental, and regulatory developments. This paper applies a multiple criteria decision analysis to prioritize investment portfolios in capacity expansion and energy security while principally studying the robustness of the prioritization to multiple uncertain and emergent scenarios. The scenarios are identified through interaction with decision makers and stakeholders. The approach finds which scenarios most affect the prioritization of the portfolios and which portfolios have the greatest upside and downside potential across scenarios. The approach fosters innovation in the use of robust and efficient technologies, renewable energy sources, and cleaner energy fuels. A demonstration is provided for assessing the performance of technology portfolios constructed from investments in nine electricity generation technologies in Mexico.

Optimized planning methodologies of ASON implementation

Science.gov (United States)

Zhou, Michael M.; Tamil, Lakshman S.

2005-02-01

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

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

Vulnerability effects of passengers' intermodal transfer distance preference and subway expansion on complementary urban public transportation systems

International Nuclear Information System (INIS)

Hong, Liu; Yan, Yongze; Ouyang, Min; Tian, Hui; He, Xiaozheng

2017-01-01

The vulnerability studies on urban public transportation systems have attracted growing attentions in recent years, due to their important role in the economy development of a city and the well-beings of its citizens. This paper proposes a vulnerability model of complementary urban public transportation systems (CUPTSs) composed of bus systems and subway systems, with the consideration of passengers’ intermodal transfer distance preference (PITDP) to capture different levels of complementary strength between the two systems. Based on the model, this paper further introduces a CUPTSs-aimed vulnerability analysis method from two specific aspects: (a) vulnerability effects of different PITDP values, which facilitate the design of policies to change PITDP to reduce system vulnerability; (b) vulnerability effects of different subway expansion plans, which facilitate the vulnerability investigation of current expansion plan and the identification of the optimal expansion plan from the system vulnerability perspective. The proposed CUPTSs-aimed vulnerability analysis method is applied to investigate the complementary bus and subway systems in the city of Wuhan, China. The insights from this study are helpful to analyze other CUPTSs for valuable planning suggestions from the vulnerability perspective. - Highlights: • We model complementary urban public transportation systems’ (CUPTSs) vulnerability. • We use a PITDP metric to capture different levels of complementary relationship. • We study vulnerability under different PITDP and different subway expansion plans. • We analyze dynamic vulnerability of CUPTSs during their expansion process.

Classical-Equivalent Bayesian Portfolio Optimization for Electricity Generation Planning

Directory of Open Access Journals (Sweden)

Hellinton H. Takada

2018-01-01

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

Capacity expansion of stochastic power generation under two-stage electricity markets

DEFF Research Database (Denmark)

Pineda, Salvador; Morales González, Juan Miguel

2016-01-01

are first formulated from the standpoint of a social planner to characterize a perfectly competitive market. We investigate the effect of two paradigmatic market designs on generation expansion planning: a day-ahead market that is cleared following a conventional cost merit-order principle, and an ideal...... of stochastic power generating units. This framework includes the explicit representation of a day-ahead and a balancing market-clearing mechanisms to properly capture the impact of forecast errors of power production on the short-term operation of a power system. The proposed generation expansion problems...... market-clearing procedure that determines day-ahead dispatch decisions accounting for their impact on balancing operation costs. Furthermore, we reformulate the proposed models to determine the optimal expansion decisions that maximize the profit of a collusion of stochastic power producers in order...

Therapeutic treatment plan optimization with probability density-based dose prescription

International Nuclear Information System (INIS)

Lian Jun; Cotrutz, Cristian; Xing Lei

2003-01-01

The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process

SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

Energy Technology Data Exchange (ETDEWEB)

Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B [University Medical Center Utrecht, Utrecht (Netherlands); Breedveld, S; Sharfo, A; Heijmen, B [Erasmus University Medical Center Rotterdam, Rotterdam (Netherlands)

2016-06-15

Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan

SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

International Nuclear Information System (INIS)

Kontaxis, C; Bol, G; Lagendijk, J; Raaymakers, B; Breedveld, S; Sharfo, A; Heijmen, B

2016-01-01

Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certain percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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.

Comparison of optimization algorithms in intensity-modulated radiation therapy planning

Science.gov (United States)

Kendrick, Rachel

Intensity-modulated radiation therapy is used to better conform the radiation dose to the target, which includes avoiding healthy tissue. Planning programs employ optimization methods to search for the best fluence of each photon beam, and therefore to create the best treatment plan. The Computational Environment for Radiotherapy Research (CERR), a program written in MATLAB, was used to examine some commonly-used algorithms for one 5-beam plan. Algorithms include the genetic algorithm, quadratic programming, pattern search, constrained nonlinear optimization, simulated annealing, the optimization method used in Varian EclipseTM, and some hybrids of these. Quadratic programing, simulated annealing, and a quadratic/simulated annealing hybrid were also separately compared using different prescription doses. The results of each dose-volume histogram as well as the visual dose color wash were used to compare the plans. CERR's built-in quadratic programming provided the best overall plan, but avoidance of the organ-at-risk was rivaled by other programs. Hybrids of quadratic programming with some of these algorithms seems to suggest the possibility of better planning programs, as shown by the improved quadratic/simulated annealing plan when compared to the simulated annealing algorithm alone. Further experimentation will be done to improve cost functions and computational time.

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

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

Science.gov (United States)

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

2012-01-01

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

Transport of natural gas; criterions for the infrastructure planning

International Nuclear Information System (INIS)

Unidad de Planeacion Minero Energetica, UPME

1999-01-01

The planning of the expansion of transport of natural gas system; should keep in mind the changes that are happening in the structure of this industry in the country. In this respect, it is growing the number of actors private present in her, what determines a indicative type planning, whose main objective is to serve as information or guide in decisions of investment involved agents in the maintenance and the amplification of the net of transport for the national supply of natural gas. An indicative plan has objectives different to those of an operative plan of short term. While this last search to establish a program of adjustments to manage commitments of transport and to maintain, this way, the validity of the gas pipeline, The indicative plan of transport is guided to quantify the intensity of the financial effort that is required so that the capacity of the gas pipeline net, responds to the prospective growth of the gas industry. In other words, the indicative plan should contribute to identify the type of works and the one mounts of the investments that the transport of gas system needs in the long term. In this sense, it is important to specify the function objective that will optimize, this precision it should take into account, in our case, the foreseen expansion of the electric sector, because this it depends in good measure of the costs and of the geographical readiness of fuels as the natural gas and the coal. Said otherwise, the function objective that should be optimized involves the expansion of the net of transport of natural gas and the expansion of the generation capacity simultaneously and of the infrastructure of electricity transmission

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

Science.gov (United States)

Lanese, Bethany G; Oglesby, Willie H

2016-01-01

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

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.

216-B-3 expansion ponds closure plan

International Nuclear Information System (INIS)

1994-10-01

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

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.

A multicriteria framework with voxel-dependent parameters for radiotherapy treatment plan optimization

International Nuclear Information System (INIS)

Zarepisheh, Masoud; Uribe-Sanchez, Andres F.; Li, Nan; Jia, Xun; Jiang, Steve B.

2014-01-01

Purpose: To establish a new mathematical framework for radiotherapy treatment optimization with voxel-dependent optimization parameters. Methods: In the treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for a set of the objective functions associated to the organs. Recent discoveries indicate that adjusting parameters associated with each voxel may lead to better plan quality. However, it is still unclear regarding the mathematical reasons behind it. Furthermore, questions about the objective function selection and parameter adjustment to assure Pareto optimality as well as the relationship between the optimal solutions obtained from the organ-based and voxel-based models remain unanswered. To answer these questions, the authors establish in this work a new mathematical framework equipped with two theorems. Results: The new framework clarifies the different consequences of adjusting organ-dependent and voxel-dependent parameters for the treatment plan optimization of radiation therapy, as well as the impact of using different objective functions on plan qualities and Pareto surfaces. The main discoveries are threefold: (1) While in the organ-based model the selection of the objective function has an impact on the quality of the optimized plans, this is no longer an issue for the voxel-based model since the Pareto surface is independent of the objective function selection and the entire Pareto surface could be generated as long as the objective function satisfies certain mathematical conditions; (2) All Pareto solutions generated by the organ-based model with different objective functions are parts of a unique Pareto surface generated by the voxel-based model with any appropriate objective function; (3) A much larger Pareto surface is explored by adjusting voxel-dependent parameters than by adjusting organ-dependent parameters, possibly

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.

Optimization of Gamma Knife treatment planning via guided evolutionary simulated annealing

International Nuclear Information System (INIS)

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

2001-01-01

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

Optimization of rotational radiotherapy treatment planning

International Nuclear Information System (INIS)

Tulovsky, Vladimir; Ringor, Michael; Papiez, Lech

1995-01-01

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

Optimization in underground mine planning - developments and opportunities

OpenAIRE

Musingwini, C.

2016-01-01

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

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)

Energy-Performance as a driver for optimal production planning

International Nuclear Information System (INIS)

Salahi, Niloofar; Jafari, Mohsen A.

2016-01-01

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

Software for CATV Design and Frequency Plan Optimization

OpenAIRE

Hala, O.

2007-01-01

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

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.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Optimization and Control of Electric Power Systems

Energy Technology Data Exchange (ETDEWEB)

Lesieutre, Bernard C. [Univ. of Wisconsin, Madison, WI (United States); Molzahn, Daniel K. [Univ. of Wisconsin, Madison, WI (United States)

2014-10-17

The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.

High-resolution temperature-based optimization for hyperthermia treatment planning

International Nuclear Information System (INIS)

Kok, H P; Haaren, P M A van; Kamer, J B Van de; Wiersma, J; Dijk, J D P Van; Crezee, J

2005-01-01

In regional hyperthermia, optimization techniques are valuable in order to obtain amplitude/phase settings for the applicators to achieve maximal tumour heating without toxicity to normal tissue. We implemented a temperature-based optimization technique and maximized tumour temperature with constraints on normal tissue temperature to prevent hot spots. E-field distributions are the primary input for the optimization method. Due to computer limitations we are restricted to a resolution of 1 x 1 x 1 cm 3 for E-field calculations, too low for reliable treatment planning. A major problem is the fact that hot spots at low-resolution (LR) do not always correspond to hot spots at high-resolution (HR), and vice versa. Thus, HR temperature-based optimization is necessary for adequate treatment planning and satisfactory results cannot be obtained with LR strategies. To obtain HR power density (PD) distributions from LR E-field calculations, a quasi-static zooming technique has been developed earlier at the UMC Utrecht. However, quasi-static zooming does not preserve phase information and therefore it does not provide the HR E-field information required for direct HR optimization. We combined quasi-static zooming with the optimization method to obtain a millimetre resolution temperature-based optimization strategy. First we performed a LR (1 cm) optimization and used the obtained settings to calculate the HR (2 mm) PD and corresponding HR temperature distribution. Next, we performed a HR optimization using an estimation of the new HR temperature distribution based on previous calculations. This estimation is based on the assumption that the HR and LR temperature distributions, though strongly different, respond in a similar way to amplitude/phase steering. To verify the newly obtained settings, we calculate the corresponding HR temperature distribution. This method was applied to several clinical situations and found to work very well. Deviations of this estimation method for

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

NARCIS (Netherlands)

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

2011-01-01

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

Clinical treatment planning optimization by Powell's method for gamma unit treatment system

International Nuclear Information System (INIS)

Yan Yulong; Shu Huazhong; Bao Xudong; Luo Limin; Bai Yi

1997-01-01

Purpose: This article presents a new optimization method for stereotactic radiosurgery treatment planning for gamma unit treatment system. Methods and Materials: The gamma unit has been utilized in stereotactic radiosurgery for about 30 years, but the usual procedure for a physician-physicist team to design a treatment plan is a trial-and-error approach. Isodose curves are viewed on two-dimensional computed tomography (CT) or magnetic resonance (MR) image planes, which is not only time consuming but also seldom achieves the optimal treatment plan, especially when the isocenter weights are regarded. We developed a treatment-planning system on a computer workstation in which Powell's optimization method is realized. The optimization process starts with the initial parameters (the number of iso centers as well as corresponding 3D iso centers' coordinates, collimator sizes, and weight factors) roughly determined by the physician-physicist team. The objective function can be changed to consider protection of sensitive tissues. Results: We use the plan parameters given by a well-trained physician-physicist team, or ones that the author give roughly as the initial parameters for the optimization procedure. Dosimetric results of optimization show a better high dose-volume conformation to the target volume compared to the doctor's plan. Conclusion: This method converges quickly and is not sensitive to the initial parameters. It achieves an excellent conformation of the estimated isodose curves with the contours of the target volume. If the initial parameters are varied, there will be a little difference in parameters' configuration, but the dosimetric results proved almost to be the same

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.

Software for CATV Design and Frequency Plan Optimization

Directory of Open Access Journals (Sweden)

O. Hala

2007-09-01

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

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

International Nuclear Information System (INIS)

2015-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1993-12-31

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

Preliminary Findings of the South Africa Power System Capacity Expansion and Operational Modelling Study: Preprint

Energy Technology Data Exchange (ETDEWEB)

Reber, Timothy J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Chartan, Erol Kevin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Brinkman, Gregory L [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-01-01

Wind and solar power contract prices have recently become cheaper than many conventional new-build alternatives in South Africa and trends suggest a continued increase in the share of variable renewable energy (vRE) on South Africa's power system with coal technology seeing the greatest reduction in capacity, see 'Figure 6: Percentage share by Installed Capacity (MW)' in [1]. Hence it is essential to perform a state-of-the-art grid integration study examining the effects of these high penetrations of vRE on South Africa's power system. Under the 21st Century Power Partnership (21CPP), funded by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has significantly augmented existing models of the South African power system to investigate future vRE scenarios. NREL, in collaboration with Eskom's Planning Department, further developed, tested and ran a combined capacity expansion and operational model of the South African power system including spatially disaggregated detail and geographical representation of system resources. New software to visualize and interpret modelling outputs has been developed, and scenario analysis of stepwise vRE build targets reveals new insight into associated planning and operational impacts and costs. The model, built using PLEXOS, is split into two components, firstly a capacity expansion model and secondly a unit commitment and economic dispatch model. The capacity expansion model optimizes new generation decisions to achieve the lowest cost, with a full understanding of capital cost and an approximated understanding of operational costs. The operational model has a greater set of detailed operational constraints and is run at daily resolutions. Both are run from 2017 through 2050. This investigation suggests that running both models in tandem may be the most effective means to plan the least cost South African power system as build plans seen to be more expensive than optimal by the

Optimization in radiotherapy treatment planning thanks to a fast dose calculation method

International Nuclear Information System (INIS)

Yang, Mingchao

2014-01-01

This thesis deals with the radiotherapy treatments planning issue which need a fast and reliable treatment planning system (TPS). The TPS is composed of a dose calculation algorithm and an optimization method. The objective is to design a plan to deliver the dose to the tumor while preserving the surrounding healthy and sensitive tissues. The treatment planning aims to determine the best suited radiation parameters for each patient's treatment. In this thesis, the parameters of treatment with IMRT (Intensity modulated radiation therapy) are the beam angle and the beam intensity. The objective function is multi-criteria with linear constraints. The main objective of this thesis is to demonstrate the feasibility of a treatment planning optimization method based on a fast dose-calculation technique developed by (Blanpain, 2009). This technique proposes to compute the dose by segmenting the patient's phantom into homogeneous meshes. The dose computation is divided into two steps. The first step impacts the meshes: projections and weights are set according to physical and geometrical criteria. The second step impacts the voxels: the dose is computed by evaluating the functions previously associated to their mesh. A reformulation of this technique makes possible to solve the optimization problem by the gradient descent algorithm. The main advantage of this method is that the beam angle parameters could be optimized continuously in 3 dimensions. The obtained results in this thesis offer many opportunities in the field of radiotherapy treatment planning optimization. (author) [fr

Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qianqian; Blohm, Andrew; Liu, Bo

2017-04-01

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

A new column-generation-based algorithm for VMAT treatment plan optimization

International Nuclear Information System (INIS)

Peng Fei; Epelman, Marina A; Romeijn, H Edwin; Jia Xun; Gu Xuejun; Jiang, Steve B

2012-01-01

We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose–volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25–55 s. (paper)

Market-based transmission expansion planning by improved differential evolution

International Nuclear Information System (INIS)

Georgilakis, Pavlos S.

2010-01-01

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

Optimal design and planning of glycerol-based biorefinery supply chains under uncertainty

DEFF Research Database (Denmark)

Loureiro da Costa Lira Gargalo, Carina; Carvalho, Ana; Gernaey, Krist V.

2017-01-01

-echelon mixed integer linear programming problem is proposed based upon a previous model, GlyThink. In the new formulation, market uncertainties are taken into account at the strategic planning level. The robustness of the supply chain structures is analyzed based on statistical data provided...... by the implementation of the Monte Carlo method, where a deterministic optimization problem is solved for each scenario. Furthermore, the solution of the stochastic multi-objective optimization model, points to the Pareto set of trade-off solutions obtained when maximizing the NPV and minimizing environmental......The optimal design and planning of glycerol-based biorefinery supply chains is critical for the development and implementation of this concept in a sustainable manner. To achieve this, a decision-making framework is proposed in this work, to holistically optimize the design and planning...

System of optimization computations of five year plans in the coal industry. [USSR

Energy Technology Data Exchange (ETDEWEB)

Goyzman, E I; Korenev, V G

1980-01-01

A system of optimization computations of five year plans is set forth which was developed over a number of years at the Central Scientific Research Institute of Economics and Scientific-Technical Information of the Coal Industry. Basic principles of design and methodological approaches are given which were used in development of the systemas well as levels of administration and information links between them. The report analyzes the characteristics of problems of planning which arise at different stages of formation of the five year plans and discusses possibilities of taking into account these characteristics in optimized models. Economic formulations of problems of optimization of five year plans are given as applied to two levels of administration: at the branch level and at the level of production associations. Economic-mathematical models of optimization of five year plans are developed for each of the levels and their characteristic features described. The primary methodological principles, on the basis of which optimization models were developed are examined. An economic-mathematical model with continuous variables was developed for the branch level of planning. Volumes of recovery according to a group of shafts in the stage of normal operation (stable group) of each production enterprise are adopted as model variables. A system of limitations which includes limitations on volumes and distinguishable resources is formulated. The minimum of operating expenses, minimum of capital investments and maximum of recovery volumes for the planned period can be used as the optimization criteria. An economic-mathematical model which uses integral variable was developed for the production association level.

Optimality of profit-including prices under ideal planning.

Science.gov (United States)

Samuelson, P A

1973-07-01

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

Optimization of Investment Planning Based on Game-Theoretic Approach

Directory of Open Access Journals (Sweden)

Elena Vladimirovna Butsenko

2018-03-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

International Nuclear Information System (INIS)

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

2017-01-01

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-01

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

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)

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.

Inverse planning and optimization: a comparison of solutions

Energy Technology Data Exchange (ETDEWEB)

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

1998-09-01

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

Transmission investment and planning in deregulated market environment : a literature survey (part 2)

International Nuclear Information System (INIS)

Wen, F.; Wu, F.F.

2005-01-01

This paper is the second half of a 2-part paper that provided details of a comprehensive survey of issues related to transmission investment and expansion planning in the electricity market. Results of the survey suggested that transmission regulation is needed to provide a fair playing field for competition and to ensure that transmission networks are optimally expanded while also meeting reliability constraints. Regulations will create further incentives for cost reduction while ensuring that regulated firms have assurance of cost recovery. Transmission planning should be controlled or monitored by a government organization or regulator. Legislation is needed to ensure that regulatory authorities can enforce reliability criteria. Mandatory reliability standards and metrics for reliability services should be implemented. The economic benefits of transmission expansion in a deregulated market should be modelled using non-deterministic approaches. It was concluded that transmission expansion plans should be able to meet future transmission capacity requirements, secure returns on investment, and ensure reliability levels for customers. Various international transmission expansion plans were also provided. 38 refs

An optimization planning technique for Suez Canal Network in Egypt

Energy Technology Data Exchange (ETDEWEB)

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

2010-02-15

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

Resampling: An optimization method for inverse planning in robotic radiosurgery

International Nuclear Information System (INIS)

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

2006-01-01

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

Planning regional energy system in association with greenhouse gas mitigation under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Li, Y.P.; Huang, G.H. [Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing 102206 (China); Chen, X. [Key Laboratory of Oasis Ecology and Desert Environment, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011 (China)

2011-03-15

Greenhouse gas (GHG) concentrations are expected to continue to rise due to the ever-increasing use of fossil fuels and ever-boosting demand for energy. This leads to inevitable conflict between satisfying increasing energy demand and reducing GHG emissions. In this study, an integrated fuzzy-stochastic optimization model (IFOM) is developed for planning energy systems in association with GHG mitigation. Multiple uncertainties presented as probability distributions, fuzzy-intervals and their combinations are allowed to be incorporated within the framework of IFOM. The developed method is then applied to a case study of long-term planning of a regional energy system, where integer programming (IP) technique is introduced into the IFOM to facilitate dynamic analysis for capacity-expansion planning of energy-production facilities within a multistage context to satisfy increasing energy demand. Solutions related fuzzy and probability information are obtained and can be used for generating decision alternatives. The results can not only provide optimal energy resource/service allocation and capacity-expansion plans, but also help decision-makers identify desired policies for GHG mitigation with a cost-effective manner. (author)

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...

Maintenance optimization plan for essential equipment reliability

International Nuclear Information System (INIS)

Steffen, D.H.

1996-02-01

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

Spatial planning via extremal optimization enhanced by cell-based local search

International Nuclear Information System (INIS)

Sidiropoulos, Epaminondas

2014-01-01

A new treatment is presented for land use planning problems by means of extremal optimization in conjunction to cell-based neighborhood local search. Extremal optimization, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper it complements extremal optimization in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific characteristic problem. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning. The present treatment yields significant compactness values as emergent results

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

Science.gov (United States)

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

2014-09-16

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

Pre-optimization of radiotherapy treatment planning: an artificial neural network classification aided technique

International Nuclear Information System (INIS)

Hosseini-Ashrafi, M.E.; Bagherebadian, H.; Yahaqi, E.

1999-01-01

A method has been developed which, by using the geometric information from treatment sample cases, selects from a given data set an initial treatment plan as a step for treatment plan optimization. The method uses an artificial neural network (ANN) classification technique to select a best matching plan from the 'optimized' ANN database. Separate back-propagation ANN classifiers were trained using 50, 60 and 77 examples for three groups of treatment case classes (up to 21 examples from each class were used). The performance of the classifiers in selecting the correct treatment class was tested using the leave-one-out method; the networks were optimized with respect their architecture. For the three groups used in this study, successful classification fractions of 0.83, 0.98 and 0.93 were achieved by the optimized ANN classifiers. The automated response of the ANN may be used to arrive at a pre-plan where many treatment parameters may be identified and therefore a significant reduction in the steps required to arrive at the optimum plan may be achieved. Treatment planning 'experience' and also results from lengthy calculations may be used for training the ANN. (author)

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

Science.gov (United States)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU

TH-CD-209-06: LET-Based Adjustment of IMPT Plans Using Prioritized Optimization

Energy Technology Data Exchange (ETDEWEB)

Unkelbach, J; Giantsoudi, D; Paganetti, H [Massachusetts General Hospital, Boston, MA (United States); Botas, P [Massachusetts General Hospital, Boston, MA (United States); Heidelberg University, Heidelberg, DE (Germany); Qin, N; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

2016-06-15

Purpose: In-vitro experiments suggest an increase in proton relative biological effectiveness (RBE) towards the end of range. However, proton treatment planning and dose reporting for clinical outcome assessment has been based on physical dose and constant RBE. Therefore, treatment planning for intensity-modulated proton therapy (IMPT) is unlikely to transition radically to pure RBE-based planning. We suggest a hybrid approach where treatment plans are initially created based on physical dose constraints and prescriptions, and are subsequently altered to avoid high linear energy transfer (LET) in critical structures while limiting the degradation of the physical dose distribution. Methods: To allow fast optimization based on dose and LET we extended a GPU-based Monte-Carlo code towards providing dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of physical dose and LET (LETxD). To first approximation, LETxD represents a measure of the additional biological dose that is caused by high LET. Regarding optimization techniques, LETxD has the advantage of being a linear function of the pencil beam intensities. Results: The method is applicable to treatments where serial critical structures with maximum dose constraint are located in or near the target. We studied intra-cranial tumors (high-grade meningiomas, base-of-skull chordomas) where the target (CTV) overlaps with the brainstem and optic structures. Often, high LETxD in critical structures can be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based re-optimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose

Reliability-Based Optimal Design of Experiment Plans for Offshore Structures

DEFF Research Database (Denmark)

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

1993-01-01

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

TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization

Energy Technology Data Exchange (ETDEWEB)

Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States)

2014-06-15

Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.

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

Science.gov (United States)

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

2010-11-01

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

Coverage-based constraints for IMRT optimization

Science.gov (United States)

Mescher, H.; Ulrich, S.; Bangert, M.

2017-09-01

Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities q(\\hat{d}, \\hat{v}) of covering a specific target volume fraction \\hat{v} with a certain dose \\hat{d} . Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.

A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

Science.gov (United States)

Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2015-04-07

Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation

An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.

Science.gov (United States)

Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P

2012-01-01

The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example

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.

Planning of Distribution Networks in Baghdad City

Directory of Open Access Journals (Sweden)

Thamir M. Abdul-Wahhab

2015-02-01

Full Text Available Planning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development. Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance. The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city based on the powerful and efficient CYMDist software as a tool for the simulation and analysis of the network. The planning method proposed in this thesis is to reach the optimum operating conditions of the network by combining the network reconfiguration in sequence with the insertion of capacitors with optimal sizing and locations. The optimum performance of the network is achieved by reducing losses, improving voltage profile and alleviating overload for transformers and cables.

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...

Optimal planning of gas turbine cogeneration system based on linear programming. Paper no. IGEC-1-ID09

International Nuclear Information System (INIS)

Oh, S.-D.; Kwak, H.-Y.

2005-01-01

An optimal planning for gas turbine cogeneration system has been studied. The planning problem considered in this study is to determine the optimal configuration of the system equipments and optimal operational policy of the system when the annual energy demands of electric power, heat and cooling are given a priori. The main benefit of the optimal planning is to minimize operational costs and to save energy by efficient energy utilization. A mixed-integer linear programming and the branch and bound algorithm have been adopted to obtain the optimal solution. Both the optimal configuration of the system equipments and the optimal operation policy has been obtained based on annual cost method. The planning method employed here may be applied to the planning problem of the cogeneration plant to any specific building or hotel. (author)

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

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...

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-07-15

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

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

International Nuclear Information System (INIS)

Zhou Jun

2009-01-01

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

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

Science.gov (United States)

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

2014-01-01

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

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

DEFF Research Database (Denmark)

Awasthi, Abhishek; Venkitusamy, Karthikeyan; Padmanaban, Sanjeevikumar

2017-01-01

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

SU-F-T-337: Accounting for Patient Motion During Volumetric Modulated Ac Therapy (VMAT) Planning for Post Mastectomy Chest Wall Irradiation

Energy Technology Data Exchange (ETDEWEB)

Hernandez, M; Fontenot, J [Mary Bird Perkins Cancer Center, Baton Rouge, LA (United States); Heins, D [Louisiana State University, Baton Rouge, LA (United States)

2016-06-15

Purpose: To evaluate two dose optimization strategies for maintaining target volume coverage of inversely-planned post mastectomy radiotherapy (PMRT) plans during patient motion. Methods: Five patients previously treated with VMAT for PMRT at our clinical were randomly selected for this study. For each patient, two plan optimization strategies were compared. Plan 1 was optimized to a volume that included the physician’s planning target volume (PTV) plus an expansion up to 0.3 cm from the bolus surface. Plan 2 was optimized to the PTV plus an expansion up to 0.3 cm from the patient surface (i.e., not extending into the bolus). VMAT plans were optimized to deliver 95% of the prescription to 95% of the PTV while sparing organs at risk based on clinical dose limits. PTV coverage was then evaluated following the simulation of patient shifts by 1.0 cm in the anterior and posterior directions using the treatment planning system. Results: Posterior patient shifts produced a difference in D95% of around 11% in both planning approaches from the non-shifted dose distributions. Coverage of the medial and lateral borders of the evaluation volume was reduced in both the posteriorly shifted plans (Plan 1 and Plan 2). Anterior patient shifts affected Plan 2 more than Plan 1 with a difference in D95% of 1% for Plan 1 versus 6% for Plan 2 from the non-shifted dose distributions. The least variation in PTV dose homogeneity for both shifts was obtained with Plan 1. However, all posteriorly shifted plans failed to deliver 95% of the prescription to 95% of the PTV. Whereas, only a few anteriorly shifted plans failed this criteria. Conclusion: The results of this study suggest both planning volume methods are sensitive to patient motion, but that a PTV extended into a bolus volume is slightly more robust for anterior patient shifts.

SU-F-T-337: Accounting for Patient Motion During Volumetric Modulated Ac Therapy (VMAT) Planning for Post Mastectomy Chest Wall Irradiation

International Nuclear Information System (INIS)

Hernandez, M; Fontenot, J; Heins, D

2016-01-01

Purpose: To evaluate two dose optimization strategies for maintaining target volume coverage of inversely-planned post mastectomy radiotherapy (PMRT) plans during patient motion. Methods: Five patients previously treated with VMAT for PMRT at our clinical were randomly selected for this study. For each patient, two plan optimization strategies were compared. Plan 1 was optimized to a volume that included the physician’s planning target volume (PTV) plus an expansion up to 0.3 cm from the bolus surface. Plan 2 was optimized to the PTV plus an expansion up to 0.3 cm from the patient surface (i.e., not extending into the bolus). VMAT plans were optimized to deliver 95% of the prescription to 95% of the PTV while sparing organs at risk based on clinical dose limits. PTV coverage was then evaluated following the simulation of patient shifts by 1.0 cm in the anterior and posterior directions using the treatment planning system. Results: Posterior patient shifts produced a difference in D95% of around 11% in both planning approaches from the non-shifted dose distributions. Coverage of the medial and lateral borders of the evaluation volume was reduced in both the posteriorly shifted plans (Plan 1 and Plan 2). Anterior patient shifts affected Plan 2 more than Plan 1 with a difference in D95% of 1% for Plan 1 versus 6% for Plan 2 from the non-shifted dose distributions. The least variation in PTV dose homogeneity for both shifts was obtained with Plan 1. However, all posteriorly shifted plans failed to deliver 95% of the prescription to 95% of the PTV. Whereas, only a few anteriorly shifted plans failed this criteria. Conclusion: The results of this study suggest both planning volume methods are sensitive to patient motion, but that a PTV extended into a bolus volume is slightly more robust for anterior patient shifts.

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.

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

Science.gov (United States)

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

2013-09-01

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

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.

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

International Nuclear Information System (INIS)

Breedveld, Sebastiaan; Storchi, Pascal R. M.; Voet, Peter W. J.; Heijmen, Ben J. M.

2012-01-01

Purpose: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. Methods: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions between patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al.[Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. Results: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a

Multiobjective optimization with a modified simulated annealing algorithm for external beam radiotherapy treatment planning

International Nuclear Information System (INIS)

Aubry, Jean-Francois; Beaulieu, Frederic; Sevigny, Caroline; Beaulieu, Luc; Tremblay, Daniel

2006-01-01

Inverse planning in external beam radiotherapy often requires a scalar objective function that incorporates importance factors to mimic the planner's preferences between conflicting objectives. Defining those importance factors is not straightforward, and frequently leads to an iterative process in which the importance factors become variables of the optimization problem. In order to avoid this drawback of inverse planning, optimization using algorithms more suited to multiobjective optimization, such as evolutionary algorithms, has been suggested. However, much inverse planning software, including one based on simulated annealing developed at our institution, does not include multiobjective-oriented algorithms. This work investigates the performance of a modified simulated annealing algorithm used to drive aperture-based intensity-modulated radiotherapy inverse planning software in a multiobjective optimization framework. For a few test cases involving gastric cancer patients, the use of this new algorithm leads to an increase in optimization speed of a little more than a factor of 2 over a conventional simulated annealing algorithm, while giving a close approximation of the solutions produced by a standard simulated annealing. A simple graphical user interface designed to facilitate the decision-making process that follows an optimization is also presented

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.

Surgical Splint Design Influences Transverse Expansion in Segmental Maxillary Osteotomies

DEFF Research Database (Denmark)

Stokbro, Kasper; Aagaard, Esben; Torkov, Peter

2017-01-01

splint designs on achieving the planned transverse expansion in bimaxillary surgery with segmental maxillary procedures. Materials and Methods: Forty-two participants were included in a retrospective observational study. All participants had completed virtually planned bimaxillary surgery with 3-piece......Purpose: In segmental maxillary procedures, it is imperative to obtain as much of the planned expansion as possible. Lack of obtained expansion, in addition to late relapse after splint removal, can result in relapse of the posterior crossbite. This study investigated the influence of 2 surgical...... maxillary segmentation. The primary outcome variable was the transverse expansion obtained, measured as the expansion between the maxillary first molars on preoperative and postoperative cone-beam computed tomograms. The postoperative scan was performed 1 week after surgery with the splint still in place...

Electricity system expansion studies to consider uncertainties and interactions in restructured markets

Science.gov (United States)

Jin, Shan

This dissertation concerns power system expansion planning under different market mechanisms. The thesis follows a three paper format, in which each paper emphasizes a different perspective. The first paper investigates the impact of market uncertainties on a long term centralized generation expansion planning problem. The problem is modeled as a two-stage stochastic program with uncertain fuel prices and demands, which are represented as probabilistic scenario paths in a multi-period tree. Two measurements, expected cost (EC) and Conditional Value-at-Risk (CVaR), are used to minimize, respectively, the total expected cost among scenarios and the risk of incurring high costs in unfavorable scenarios. We sample paths from the scenario tree to reduce the problem scale and determine the sufficient number of scenarios by computing confidence intervals on the objective values. The second paper studies an integrated electricity supply system including generation, transmission and fuel transportation with a restructured wholesale electricity market. This integrated system expansion problem is modeled as a bi-level program in which a centralized system expansion decision is made in the upper level and the operational decisions of multiple market participants are made in the lower level. The difficulty of solving a bi-level programming problem to global optimality is discussed and three problem relaxations obtained by reformulation are explored. The third paper solves a more realistic market-based generation and transmission expansion problem. It focuses on interactions among a centralized transmission expansion decision and decentralized generation expansion decisions. It allows each generator to make its own strategic investment and operational decisions both in response to a transmission expansion decision and in anticipation of a market price settled by an Independent System Operator (ISO) market clearing problem. The model poses a complicated tri-level structure

AI-guided parameter optimization in inverse treatment planning

International Nuclear Information System (INIS)

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

2003-01-01

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

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

International Nuclear Information System (INIS)

Yarmand, Hamed; Winey, Brian; Craft, David

2013-01-01

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. (paper)

Cost estimating issues in the Russian integrated system planning context

International Nuclear Information System (INIS)

Allentuck, J.

1996-01-01

An important factor in the credibility of an optimal capacity expansion plan is the accuracy of cost estimates given the uncertainty of future economic conditions. This paper examines the problems associated with estimating investment and operating costs in the Russian nuclear power context over the period 1994 to 2010

SVC Planning in Large–scale Power Systems via a Hybrid Optimization Method

DEFF Research Database (Denmark)

Yang, Guang ya; Majumder, Rajat; Xu, Zhao

2009-01-01

The research on allocation of FACTS devices has attracted quite a lot interests from various aspects. In this paper, a hybrid model is proposed to optimise the number, location as well as the parameter settings of static Var compensator (SVC) deployed in large–scale power systems. The model...... utilises the result of vulnerability assessment for determining the candidate locations. A hybrid optimisation method including two stages is proposed to find out the optimal solution of SVC in large– scale planning problem. In the first stage, a conventional genetic algorithm (GA) is exploited to generate...... a candidate solution pool. Then in the second stage, the candidates are presented to a linear planning model to investigate the system optimal loadability, hence the optimal solution for SVC planning can be achieved. The method is presented to IEEE 300–bus system....

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

Science.gov (United States)

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

2018-12-01

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

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

DEFF Research Database (Denmark)

Clausen, Jens

2007-01-01

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

Simulation-optimization model for production planning in the blood supply chain.

Science.gov (United States)

Osorio, Andres F; Brailsford, Sally C; Smith, Honora K; Forero-Matiz, Sonia P; Camacho-Rodríguez, Bernardo A

2017-12-01

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

Development of a fast optimization preview in radiation treatment planning

International Nuclear Information System (INIS)

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

1996-01-01

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

94: Treatment plan optimization for conformal therapy

International Nuclear Information System (INIS)

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

1987-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-10-15

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

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

International Nuclear Information System (INIS)

Kim, Young Joo; Chang, Choong Koo

2014-01-01

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

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

International Nuclear Information System (INIS)

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

2011-01-01

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

An interactive beam-weight optimization tool for three-dimensional radiotherapy treatment planning

International Nuclear Information System (INIS)

Burba, S.; Gardey, K.; Nadobny, J.; Stalling, D.; Seebass, M.; Beier, J.; Wust, P.; Budach, V.; Felix, R.

1997-01-01

Purpose: A computer software tool has been developed to aid the treatment planner in selecting beam weights for three-dimensional radiotherapy treatment planning. An approach to plan optimization has been made that is based on the use of an iterative feasibility search algorithm combined with a quadratic convergence method that seeks a set of beam weights which satisfies all the dose constraints set by the planner. Materials and Methods: A FORTRAN module for dose calculation for radiotherapy (a VOXELPLAN modification) has been integrated into an object-oriented Silicon Graphics TM platform in an IRIS Inventor environment on basis of the OpenGL which up to now has been exclusively used for the calculation of E-field distributions in hyperthermia (HyperPlan TM ). After the successful calculation and representation of the dose distribution in the Silicon Graphics TM platform, an algorithm involving the minimization method according to the principle of quadratic convergence was developed for optimizing beam weights of a number of pre-calculated fields. The verification of the algorithms for dose calculation and dose optimization has been realized by use of a standardized interface to the program VIRTUOS as well as by the collapsed cone algorithm implemented in the commercial treatment planning system Helax TMS TM . Results: The search algorithm allows the planner to incorporate relative importance weightings to target volumes and anatomical structures, specifying, for example, that a dose constraint to the spinal cord is much more crucial to the overall evaluation of a treatment plan than a dose constraint to otherwise uninvolved soft tissue. In most cases the applied minimization method according to the model of Davidon-Fletcher-Powell showed ultimate fast convergence for a general function f(x) with continuous second derivatives and fast convergence for a positive definite quadratic function. In other cases, however, the absence of an acceptable solution may indicate

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

Study on optimization of normal plant outage work plan for nuclear power plants

International Nuclear Information System (INIS)

Aoki, Takayuki; Kodama, Noriko; Takase, Kentaro; Miya, Kenzo

2011-01-01

This paper discusses maintenance optimization in maintenance implementation stage following maintenance planning stage in nuclear power plants and proposes a methodology to get an optimum maintenance work plan. As a result of consideration, the followings were obtained. (1) The quantitative evaluation methodology for optimizing maintenance work plan in nuclear power plants was developed. (2) Utilizing the above methodology, a simulation analysis of maintenance work planning for BWR's PLR and RHR systems in a normal plant outage was performed. Maintenance cost calculation in several cases was carried out on the condition of smoothening man loading over the plant outage schedule as much as possible. (3) As a result of the simulation, the economical work plans having a flat man loading over the plant outage schedule were obtained. (author)

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

OpenAIRE

Soler Arnedo, Manuel Fernando

2017-01-01

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

Optimized LTE Cell Planning with Varying Spatial and Temporal User Densities

KAUST Repository

Ghazzai, Hakim; Yaacoub, Elias; Alouini, Mohamed-Slim; Dawy, Zaher; Abu Dayya, Adnan

2015-01-01

Base station deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation (4G) cellular networks using meta-heuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterwards, we implement a meta-heuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently-proposed grey wolf optimizer) to find suboptimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regards to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality of service targets are always reached even for large-scale problems.

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.

Economic Instruments and the Pollution Impact of the 2006-2010 Vietnam Socio-Economic Development Plan

DEFF Research Database (Denmark)

Jensen, Henning Tarp; Tarp, Finn; Xuan, Hong Vu

plan for Vietnam (Jensen et al.; 2008). The current study demonstratesthat effective implementation and moderate expansion of optimal emission charges, under certain conditions, could have been used, as part of the 2006-2010 SEDP development plan, to control pollution emissions at 2005 levels. Moreover...... plans, in order to control pollution emissions as development progresses in Vietnam.......The current study derives optimal growth paths for pollution emission charges, in order to control future water pollution emissions in the Vietnamese manufacturing sector. The study builds on a prior study, which estimated the manufacturing sector pollution impact of the 2006- 2010 SEDP development...

An algorithmic interactive planning framework in support of sustainable technologies

Science.gov (United States)

Prica, Marija D.

This thesis addresses the difficult problem of generation expansion planning that employs the most effective technologies in today's changing electric energy industry. The electrical energy industry, in both the industrialized world and in developing countries, is experiencing transformation in a number of different ways. This transformation is driven by major technological breakthroughs (such as the influx of unconventional smaller-scale resources), by industry restructuring, changing environmental objectives, and the ultimate threat of resource scarcity. This thesis proposes a possible planning framework in support of sustainable technologies where sustainability is viewed as a mix of multiple attributes ranging from reliability and environmental impact to short- and long-term efficiency. The idea of centralized peak-load pricing, which accounts for the tradeoffs between cumulative operational effects and the cost of new investments, is the key concept in support of long-term planning in the changing industry. To start with, an interactive planning framework for generation expansion is posed as a distributed decision-making model. In order to reconcile the distributed sub-objectives of different decision makers with system-wide sustainability objectives, a new concept of distributed interactive peak load pricing is proposed. To be able to make the right decisions, the decision makers must have sufficient information about the estimated long-term electricity prices. The sub-objectives of power plant owners and load-serving entities are profit maximization. Optimized long-term expansion plans based on predicted electricity prices are communicated to the system-wide planning authority as long-run bids. The long-term expansion bids are cleared by the coordinating planner so that the system-wide long-term performance criteria are satisfied. The interactions between generation owners and the coordinating planning authority are repeated annually. We view the proposed

An optimal control approach to manpower planning problem

Directory of Open Access Journals (Sweden)

H. W. J. Lee

2001-01-01

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

Integrating robust timetabling in line plan optimization for railway systems

DEFF Research Database (Denmark)

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

2017-01-01

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

Temporo-spatial IMRT optimization: concepts, implementation and initial results

International Nuclear Information System (INIS)

Trofimov, Alexei; Rietzel, Eike; Lu Hsiaoming; Martin, Benjamin; Jiang, Steve; Chen, George T Y; Bortfeld, Thomas

2005-01-01

With the recent availability of 4D-CT, the accuracy of information on internal organ motion during respiration has improved significantly. We investigate the utility of organ motion information in IMRT treatment planning, using an in-house prototype optimization system. Four approaches are compared: (1) planning with optimized margins, based on motion information; (2) the 'motion kernel' approach, in which a more accurate description of the dose deposit from a pencil beam to a moving target is achieved either through time-weighted averaging of influence matrices, calculated for different instances of anatomy (subsets of 4D-CT data, corresponding to various phases of motion) or through convolution of the pencil beam kernel with the probability density function describing the target motion; (3) optimal gating, or tracking with beam intensity maps optimized independently for each instance of anatomy; and (4) optimal tracking with beam intensity maps optimized simultaneously for all instances of anatomy. The optimization is based on a gradient technique and can handle both physical (dose-volume) and equivalent uniform dose constraints. Optimization requires voxel mapping from phase to phase in order to score the dose in individual voxels as they move. The results show that, compared to the other approaches, margin expansion has a significant disadvantage by substantially increasing the integral dose to patient. While gating or tracking result in the best dose conformation to the target, the former elongates treatment time, and the latter significantly complicates the delivery procedure. The 'motion kernel' approach does not provide a dosimetric advantage, compared to optimal tracking or gating, but might lead to more efficient delivery. A combination of gating with the 'motion kernel' or margin expansion approach will increase the duty cycle and may provide one with the most efficient solution, in terms of complexity of the delivery procedure and dose conformality to

Optimizing production and imperfect preventive maintenance planning's integration in failure-prone manufacturing systems

International Nuclear Information System (INIS)

Aghezzaf, El-Houssaine; Khatab, Abdelhakim; Tam, Phuoc Le

2016-01-01

This paper investigates the issue of integrating production and maintenance planning in a failure-prone manufacturing system. It is assumed that the system's operating state is stochastically predictable, in terms of its operating age, and that it can accordingly be preventively maintained during preplanned periods. Preventive maintenance is assumed to be imperfect, that is when performed, it brings the manufacturing system to an operating state that lies between ‘as bad as old’ and ‘as good as new’. Only an overhauling of the system brings it to a ‘as good as new’ operating state again. A practical integrated production and preventive maintenance planning model, that takes into account the system's manufacturing capacity and its operational reliability state, is developed. The model is naturally formulated as a mixed-integer non-linear optimization problem, for which an extended mixed-integer linear reformulation is proposed. This reformulation, while it solves the proposed integrated planning problem to optimality, remains quite demanding in terms of computational time. A fix-and-optimize procedure, that takes advantage of some properties of the original model, is then proposed. The reformulation and the fix-and-optimize procedure are tested on some test instances adapted from those available in the literature. The results show that the proposed fix-and-optimize procedure performs quite well and opens new research direction for future improvements. - Highlights: • Integration of production planning and imperfect preventive maintenance is explored. • Imperfect maintenance is modeled using a fitting age reduction hybrid hazard rate. • A practical approximate optimization model for this integration is proposed. • The resulting naturally MINL optimization model is reformulated and solved as a MILP. • An effective fix-and-optimize procedure is proposed for large instances of this MILP.

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

International Nuclear Information System (INIS)

Feng, W.

2015-01-01

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

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

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.

Optimal farm plans for sustainable environmental and economic ...

African Journals Online (AJOL)

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

A complex systems approach to planning, optimization and decision making for energy networks

International Nuclear Information System (INIS)

Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

2008-01-01

This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock

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

Energy Technology Data Exchange (ETDEWEB)

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

1977-01-01

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

Penalized likelihood fluence optimization with evolutionary components for intensity modulated radiation therapy treatment planning

International Nuclear Information System (INIS)

Baydush, Alan H.; Marks, Lawrence B.; Das, Shiva K.

2004-01-01

A novel iterative penalized likelihood algorithm with evolutionary components for the optimization of beamlet fluences for intensity modulated radiation therapy (IMRT) is presented. This algorithm is designed to be flexible in terms of the objective function and automatically escalates dose, as long as the objective function increases and all constraints are met. For this study, the objective function employed was the product of target equivalent uniform dose (EUD) and fraction of target tissue within set homogeneity constraints. The likelihood component of the algorithm iteratively attempts to minimize the mean squared error between a homogeneous dose prescription and the actual target dose distribution. The updated beamlet fluences are then adjusted via a quadratic penalty function that is based on the dose-volume histogram (DVH) constraints of the organs at risk. The evolutionary components were included to prevent the algorithm from converging to a local maximum. The algorithm was applied to a prostate cancer dataset, with especially difficult DVH constraints on bladder, rectum, and femoral heads. Dose distributions were generated for manually selected sets of three-, four-, five-, and seven-field treatment plans. Additionally, a global search was performed to find the optimal orientations for an axial three-beam plan. The results from this optimal orientation set were compared to results for manually selected orientation (gantry angle) sets of 3- (0 deg., 90 deg., 270 deg. ), 4- (0 deg., 90 deg., 180 deg., 270 deg. ), 5- (0 deg., 50 deg., 130 deg., 230 deg., 310 deg.), and 7- (0 deg., 40 deg., 90 deg., 140 deg., 230 deg., 270 deg., 320 deg. ) field axial treatment plans. For all the plans generated, all DVH constraints were met and average optimization computation time was approximately 30 seconds. For the manually selected orientations, the algorithm was successful in providing a relatively homogeneous target dose distribution, while simultaneously satisfying

Schedule optimization study implementation plan

International Nuclear Information System (INIS)

1993-11-01

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

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.

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.

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

OpenAIRE

Tunjo Perić; Željko Mandić

2017-01-01

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

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

International Nuclear Information System (INIS)

Higgins, R. J.

2006-01-01

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

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

International Nuclear Information System (INIS)

Barragán, A. M.; Differding, S.; Lee, J. A.; Sterpin, E.; Janssens, G.

2015-01-01

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 PET ) was calculated from 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 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 PET (worst case) were above 5% of DPBN

Discrete PSO algorithm based optimization of transmission lines loading in TNEP problem

International Nuclear Information System (INIS)

Shayeghi, H.; Mahdavi, M.; Bagheri, A.

2010-01-01

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e. expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using discrete particle swarm optimization (DPSO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network and an actual transmission network of the Azerbaijan regional electric company, Iran, and the results are compared with the decimal codification genetic algorithm (DCGA) technique. The results evaluation shows that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is superior to DCGA approach.

Wind energy planning in Denmark

International Nuclear Information System (INIS)

Godtfredsen, F.; Lemming, J.; Nielsen, S.R.; Jessien, S.

1992-01-01

The total capacity of the about 3300 Danish wind turbines is approximately 450 MW. Most of the wind turbines have been erected detached or in small clusters by private citizens - especially by joint ownership. 100 MW of the capacity have been installed by the power companies, mainly in wind farms. Up till now the privately owned wind turbines have been erected without a previous planning process. Increased expansion of wind energy makes demands on physical planning, since access to suitable locations in Denmark is limited. Hence more coordination is called for between the interested parties to ensure optimal utilization of the sites allocated by the physical planning authorities. A siting committee appointed by the Government has recommended locations for additional 100 MW power company wind farms as well as a more detailed planning in each local community. The detailed planning in the municipality of Thisted is described. (au)

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

Science.gov (United States)

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

2017-05-01

Evolutionary stochastic global optimization algorithms are widely used in large-scale, nonconvex problems. However, enhancing the search efficiency and repeatability of these techniques often requires well-customized approaches. This study investigates one such approach. We use particle swarm optimization (PSO) algorithm to solve a 4D radiation therapy (RT) inverse planning problem, where the key idea is to use respiratory motion as an additional degree of freedom in lung cancer RT. The primary goal is to administer a lethal dose to the tumor target while sparing surrounding healthy tissue. Our optimization iteratively adjusts radiation fluence-weights for all beam apertures across all respiratory phases. We implement three PSO-based approaches: conventionally used unconstrained, hard-constrained, and our proposed virtual search. As proof of concept, five lung cancer patient cases are optimized over ten runs using each PSO approach. For comparison, a dynamically penalized likelihood (DPL) algorithm-a popular RT optimization technique is also implemented and used. The proposed technique significantly improves the robustness to random initialization while requiring fewer iteration cycles to converge across all cases. DPL manages to find the global optimum in 2 out of 5 RT cases over significantly more iterations. The proposed virtual search approach boosts the swarm search efficiency, and consequently, improves the optimization convergence rate and robustness for PSO. RT planning is a large-scale, nonconvex optimization problem, where finding optimal solutions in a clinically practical time is critical. Our proposed approach can potentially improve the optimization efficiency in similar time-sensitive problems.

Constrained optimal motion planning for autonomous vehicles using PRONTO

NARCIS (Netherlands)

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

2017-01-01

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

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.

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.

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.

Validity of Edgeworth expansions for realized volatility estimators

DEFF Research Database (Denmark)

Hounyo, Ulrich; Veliyev, Bezirgen

(2009). Second, we show that the validity of the Edgeworth expansions for realized volatility may not cover the optimal two-point distribution wild bootstrap proposed by Gonçalves and Meddahi (2009). Then, we propose a new optimal nonlattice distribution which ensures the second-order correctness...... of the bootstrap. Third, in the presence of microstructure noise, based on our Edgeworth expansions, we show that the new optimal choice proposed in the absence of noise is still valid in noisy data for the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009). Finally, we show how...

New transmission planning methodology for requesting proposals for wind generation

Science.gov (United States)

Isaacs, Andrew L.

The increasing interest in renewable energy technologies during the last decade has caused conventional transmission and generation expansion planning methodologies to be strained and in some cases abandoned. This is due both to the quantity of generator interconnection requests and the constraints imposed by deregulated energy industry structures. One technique used to control the influx of renewable generation while maintaining competitive principles is a Request for Proposals (RFP). However, lack of transmission planning due to a disconnection between generation and transmission owners, difficulty in identifying viable projects, and high risk for proponents stand as obstacles to the goals of an RFP. This research proposes a procedure which minimizes the effect of these obstacles; meeting the purchaser requirements for low price and combining conventional planning concepts with feedback from competitive structures. The general features of the method include definition of generation limits and study area, expansion plan design, transmission cost evaluation, optimal selection of requested generation levels, and final selection of successful proponents. The method is shown to be effective in creating an RFP where proponents are well-informed and provided with cost certainty to reduce bid price, buyers are able to determine end costs of their energy, and good expansion planning principles are maintained. A case study using a real system in New Mexico demonstrates these concepts.

Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Directory of Open Access Journals (Sweden)

B. Mashadi

Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.

Development of a Whole Body Atlas for Radiation Therapy Planning and Treatment Optimization

International Nuclear Information System (INIS)

Qatarneh, Sharif

2006-01-01

The main objective of radiation therapy is to obtain the highest possible probability of tumor cure while minimizing adverse reactions in healthy tissues. A crucial step in the treatment process is to determine the location and extent of the primary tumor and its loco regional lymphatic spread in relation to adjacent radiosensitive anatomical structures and organs at risk. These volumes must also be accurately delineated with respect to external anatomic reference points, preferably on surrounding bony structures. At the same time, it is essential to have the best possible physical and radiobiological knowledge about the radiation responsiveness of the target tissues and organs at risk in order to achieve a more accurate optimization of the treatment outcome. A computerized whole body Atlas has therefore been developed to serve as a dynamic database, with systematically integrated knowledge, comprising all necessary physical and radiobiological information about common target volumes and normal tissues. The Atlas also contains a database of segmented organs and a lymph node topography, which was based on the Visible Human dataset, to form standard reference geometry of organ systems. The reference knowledge base and the standard organ dataset can be utilized for Atlas-based image processing and analysis in radiation therapy planning and for biological optimization of the treatment outcome. Atlas-based segmentation procedures were utilized to transform the reference organ dataset of the Atlas into the geometry of individual patients. The anatomic organs and target volumes of the database can be converted by elastic transformation into those of the individual patient for final treatment planning. Furthermore, a database of reference treatment plans was started by implementing state-of-the-art biologically based radiation therapy planning techniques such as conformal, intensity modulated, and radio biologically optimized treatment planning. The computerized Atlas can

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.

Investments Portfolio Optimal Planning for industrial assets management: Method and Tool

International Nuclear Information System (INIS)

Lonchampt, Jerome; Fessart, Karine

2012-01-01

The purpose of this paper is to describe the method and tool dedicated to optimize investments planning for industrial assets. These investments may either be preventive maintenance tasks, asset enhancement or logistic investment such as spare parts purchase. The three methodological points to investigate in such an issue are: 1. The measure of the profitability of a portfolio of investments 2. The selection and planning of an optimal set of investments 3. The measure of the risk of a portfolio of investments The measure of the profitability of a set of investments in the IPOP (registered) tool is synthesised in the Net Present Value indicator. The NPV is the sum of the differences of discounted cash flows (direct costs, forced outages...) between the situations with and without a given investment. These cash flows are calculated through a pseudo-markov reliability model representing independently the components of the industrial asset and the spare parts inventories. The component model has been widely discussed over the years but the spare part model is a new one based on some approximations that will be discussed. This model, referred as the NPV function, takes for input an investments portfolio and gives its NPV. The second issue is to optimize the NPV. If all investments were independent, this optimization would be an easy calculation, unfortunately there are two sources of dependency. The first one is introduced by the spare part model, as if components are indeed independent in their reliability model, the fact that several components use the same inventory induces a dependency. The second dependency comes from economic, technical or logistic constraints, such as a global maintenance budget limit or a precedence constraint between two investments, making the aggregation of individual optimum not necessary feasible. The algorithm used to solve such a difficult optimization problem is a genetic algorithm. After a description of the features of the software a

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

Directory of Open Access Journals (Sweden)

Hui Li

2014-03-01

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

Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

Science.gov (United States)

Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

2018-03-01

The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

Resource planning and scheduling of payload for satellite with particle swarm optimization

Science.gov (United States)

Li, Jian; Wang, Cheng

2007-11-01

The resource planning and scheduling technology of payload is a key technology to realize an automated control for earth observing satellite with limited resources on satellite, which is implemented to arrange the works states of various payloads to carry out missions by optimizing the scheme of the resources. The scheduling task is a difficult constraint optimization problem with various and mutative requests and constraints. Based on the analysis of the satellite's functions and the payload's resource constraints, a proactive planning and scheduling strategy based on the availability of consumable and replenishable resources in time-order is introduced along with dividing the planning and scheduling period to several pieces. A particle swarm optimization algorithm is proposed to address the problem with an adaptive mutation operator selection, where the swarm is divided into groups with different probabilities to employ various mutation operators viz., differential evolution, Gaussian and random mutation operators. The probabilities are adjusted adaptively by comparing the effectiveness of the groups to select a proper operator. The simulation results have shown the feasibility and effectiveness of the method.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Optimal pricing and marketing planning for deteriorating items.

Directory of Open Access Journals (Sweden)

Seyed Reza Moosavi Tabatabaei

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

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

Optimal planning of multiple distributed generation sources in distribution networks: A new approach

Energy Technology Data Exchange (ETDEWEB)

AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

2011-10-15

Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

Optimal planning of multiple distributed generation sources in distribution networks: A new approach

International Nuclear Information System (INIS)

AlRashidi, M.R.; AlHajri, M.F.

2011-01-01

Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

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

International Nuclear Information System (INIS)

Becker, Nir; Soloveitchik, David; Olshansky, Moshe

2011-01-01

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

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.

Impact of using linear optimization models in dose planning for HDR brachytherapy

International Nuclear Information System (INIS)

Holm, Aasa; Larsson, Torbjoern; Carlsson Tedgren, Aasa

2012-01-01

Purpose: Dose plans generated with optimization models hitherto used in high-dose-rate (HDR) brachytherapy have shown a tendency to yield longer dwell times than manually optimized plans. Concern has been raised for the corresponding undesired hot spots, and various methods to mitigate these have been developed. The hypotheses upon this work is based are (a) that one cause for the long dwell times is the use of objective functions comprising simple linear penalties and (b) that alternative penalties, as these are piecewise linear, would lead to reduced length of individual dwell times. Methods: The characteristics of the linear penalties and the piecewise linear penalties are analyzed mathematically. Experimental comparisons between the two types of penalties are carried out retrospectively for a set of prostate cancer patients. Results: When the two types of penalties are compared, significant changes can be seen in the dwell times, while most dose-volume parameters do not differ significantly. On average, total dwell times were reduced by 4.2%, with a reduction of maximum dwell times by 25%, when the alternative penalties were used. Conclusions: The use of linear penalties in optimization models for HDR brachytherapy is one cause for the undesired long dwell times that arise in mathematically optimized plans. By introducing alternative penalties, a significant reduction in dwell times can be achieved for HDR brachytherapy dose plans. Although various measures for mitigating the long dwell times are already available, the observation that linear penalties contribute to their appearance is of fundamental interest.

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.

Optimizing Maintenance Planning in the Production Industry Using the Markovian Approach

Directory of Open Access Journals (Sweden)

B Kareem

2012-12-01

Full Text Available Maintenance is an essential activity in every manufacturing establishment, as manufacturing effectiveness counts on the functionality of production equipment and machinery in terms of their productivity and operational life. Maintenance cost minimization can be achieved by adopting an appropriate maintenance planning policy. This paper applies the Markovian approach to maintenance planning decision, thereby generating optimal maintenance policy from the identified alternatives over a specified period of time. Markov chains, transition matrices, decision processes, and dynamic programming models were formulated for the decision problem related to maintenance operations of a cable production company. Preventive and corrective maintenance data based on workloads and costs, were collected from the company and utilized in this study. The result showed variability in the choice of optimal maintenance policy that was adopted in the case study. Post optimality analysis of the process buttressed the claim. The proposed approach is promising for solving the maintenance scheduling decision problems of the company.

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.

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.

An improved DPSO with mutation based on similarity algorithm for optimization of transmission lines loading

International Nuclear Information System (INIS)

Shayeghi, H.; Mahdavi, M.; Bagheri, A.

2010-01-01

Static transmission network expansion planning (STNEP) problem acquires a principal role in power system planning and should be evaluated carefully. Up till now, various methods have been presented to solve the STNEP problem. But only in one of them, lines adequacy rate has been considered at the end of planning horizon and the problem has been optimized by discrete particle swarm optimization (DPSO). DPSO is a new population-based intelligence algorithm and exhibits good performance on solution of the large-scale, discrete and non-linear optimization problems like STNEP. However, during the running of the algorithm, the particles become more and more similar, and cluster into the best particle in the swarm, which make the swarm premature convergence around the local solution. In order to overcome these drawbacks and considering lines adequacy rate, in this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using an improved DPSO algorithm. The proposed improved DPSO is a new conception, collectivity, which is based on similarity between the particle and the current global best particle in the swarm that can prevent the premature convergence of DPSO around the local solution. The proposed method has been tested on the Garver's network and a real transmission network in Iran, and compared with the DPSO based method for solution of the TNEP problem. The results show that the proposed improved DPSO based method by preventing the premature convergence is caused that with almost the same expansion costs, the network adequacy is increased considerably. Also, regarding the convergence curves of both methods, it can be seen that precision of the proposed algorithm for the solution of the STNEP problem is more than DPSO approach.

Multicriteria plan optimization in the hands of physicians: a pilot study in prostate cancer and brain tumors.

Science.gov (United States)

Müller, Birgit S; Shih, Helen A; Efstathiou, Jason A; Bortfeld, Thomas; Craft, David

2017-11-06

The purpose of this study was to demonstrate the feasibility of physician driven planning in intensity modulated radiotherapy (IMRT) with a multicriteria optimization (MCO) treatment planning system and template based plan optimization. Exploiting the full planning potential of MCO navigation, this alternative planning approach intends to improve planning efficiency and individual plan quality. Planning was retrospectively performed on 12 brain tumor and 10 post-prostatectomy prostate patients previously treated with MCO-IMRT. For each patient, physicians were provided with a template-based generated Pareto surface of optimal plans to navigate, using the beam angles from the original clinical plans. We compared physician generated plans to clinically delivered plans (created by dosimetrists) in terms of dosimetric differences, physician preferences and planning times. Plan qualities were similar, however physician generated and clinical plans differed in the prioritization of clinical goals. Physician derived prostate plans showed significantly better sparing of the high dose rectum and bladder regions (p(D1) plans indicated higher doses for targets and brainstem (p(D1) plan comparisons physicians preferred the clinical plans more often (brain: 6:3 out of 12, prostate: 2:6 out of 10) (not statistically significant). While times of physician involvement were comparable for prostate planning, the new workflow reduced the average involved time for brain cases by 30%. Planner times were reduced for all cases. Subjective benefits, such as a better understanding of planning situations, were observed by clinicians through the insight into plan optimization and experiencing dosimetric trade-offs. We introduce physician driven planning with MCO for brain and prostate tumors as a feasible planning workflow. The proposed approach standardizes the planning process by utilizing site specific templates and integrates physicians more tightly into treatment planning. Physicians

Computer-based planning of optimal donor sites for autologous osseous grafts

Science.gov (United States)

Krol, Zdzislaw; Chlebiej, Michal; Zerfass, Peter; Zeilhofer, Hans-Florian U.; Sader, Robert; Mikolajczak, Pawel; Keeve, Erwin

2002-05-01

Bone graft surgery is often necessary for reconstruction of craniofacial defects after trauma, tumor, infection or congenital malformation. In this operative technique the removed or missing bone segment is filled with a bone graft. The mainstay of the craniofacial reconstruction rests with the replacement of the defected bone by autogeneous bone grafts. To achieve sufficient incorporation of the autograft into the host bone, precise planning and simulation of the surgical intervention is required. The major problem is to determine as accurately as possible the donor site where the graft should be dissected from and to define the shape of the desired transplant. A computer-aided method for semi-automatic selection of optimal donor sites for autografts in craniofacial reconstructive surgery has been developed. The non-automatic step of graft design and constraint setting is followed by a fully automatic procedure to find the best fitting position. In extension to preceding work, a new optimization approach based on the Levenberg-Marquardt method has been implemented and embedded into our computer-based surgical planning system. This new technique enables, once the pre-processing step has been performed, selection of the optimal donor site in time less than one minute. The method has been applied during surgery planning step in more than 20 cases. The postoperative observations have shown that functional results, such as speech and chewing ability as well as restoration of bony continuity were clearly better compared to conventionally planned operations. Moreover, in most cases the duration of the surgical interventions has been distinctly reduced.

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

Directory of Open Access Journals (Sweden)

Tunjo Perić

2017-09-01

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

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.

Optimal Risk-Based Inspection Planning for Offshore Wind Turbines

DEFF Research Database (Denmark)

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

2008-01-01

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

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

DEFF Research Database (Denmark)

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

2012-01-01

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

Optimal radiation port arrangements for hepatic tumor using 3-dimensional conformal radiotherapy planning

Energy Technology Data Exchange (ETDEWEB)

Lee, Ik Jae; Seong, Jin Sil; Shim, Su Jung; Jeong, Kyoung Keun [Yonsei Univ., Seoul (Korea, Republic of); Cho, Kwang Hwan [Sunchunhyang Univ., Buchon (Korea, Republic of)

2006-12-15

The purpose of this study was to investigate the optimal beam arrangements for hepatic tumors, according to the location of the hepatic tumor and its relationship to Organs At Risk (OARs). The virtual gross tumor volumes were divided into four groups according to the Couinaud's classification. Several plans were made for each virtual target, and these plans were compared for the Normal Tissue Complication Probabilities (NTCP). For group I, NTCP improved as the number of the beam ports increased. However, plans with more than 5 ports had little advantage. For group II, plans with the beam directions from the anterior side showed better results. Group III contained many OARs near the target, which placed restrictions on the beam-directions. Multi-directional plans yielded a higher dose to the OARs than a simple two-port plan using right anterior oblique and posterior beam (RAO/PA). For group IV, a simple RAO/PA port plan was adequate for protection of remaining liver. NTCP can significantly vary between radiotherapy plans when the location of the tumor and its neighboring OARs are taken into consideration. The results in this study of optimal beam arrangements could be a useful set of guidelines for radiotherapy of hepatic tumors.

Optimization of time and location dependent spent nuclear fuel storage capacity

International Nuclear Information System (INIS)

Macek, V.

1977-01-01

A linear spent fuel storage model is developed to identify cost-effective spent nuclear fuel storage strategies. The purpose of this model is to provide guidelines for the implementation of the optimal time-dependent spent fuel storage capacity expansion in view of the current economic and regulatory environment which has resulted in phase-out of the closed nuclear fuel cycle. Management alternatives of the spent fuel storage backlog, which is created by mismatch between spent fuel generation rate and spent fuel disposition capability, are represented by aggregate decision variables which describe the time dependent on-reactor-site and off-site spent fuel storage capacity additions, and the amount of spent fuel transferred to off-site storage facilities. Principal constraints of the model assure determination of cost optimal spent fuel storage expansion strategies, while spent fuel storage requirements are met at all times. A detailed physical and economic analysis of the essential components of the spent fuel storage problem, which precedes the model development, assures its realism. The effects of technological limitations on the on-site spent fuel storage expansion and timing of reinitiation of the spent fuel reprocessing on optimal spent fuel storage capacity expansion are investigated. The principal results of the study indicate that (a) expansion of storage capacity beyond that of currently planned facilities is necessary, and (b) economics of the post-reactor fuel cycle is extremely sensitive to the timing of reinitiation of spent fuel reprocessing. Postponement of reprocessing beyond mid-1982 may result in net negative economic liability of the back end of the nuclear fuel cycle

Economic Instruments and the Pollution Impact of the 2006-2010 Vietnam Socio-Economic Development Plan

OpenAIRE

Jensen, Henning Tarp; Tarp, Finn; Hong, Vu Xuan Nguyet; Man Hai, Nguyen; Thanh, Le Ha

2008-01-01

The current study derives optimal growth paths for pollution emission charges, in order to control future water pollution emissions in the Vietnamese manufacturing sector. The study builds on a prior study, which estimated the manufacturing sector pollution impact of the 2006- 2010 SEDP development plan for Vietnam (Jensen et al.; 2008). The current study demonstratesthat effective implementation and moderate expansion of optimal emission charges, under certain conditions, could have been use...

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

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