989 resultados para Programming, Linear, utilization


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Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

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Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

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The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.

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This paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.

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In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

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This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.

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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

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RESUMO: Introdução – A Radioterapia (RT) é uma abordagem terapêutica para tratamento de neoplasia de mama. Contudo, diferentes técnicas de irradiação (TI) podem ser usadas. Objetivos – Comparar 4 TI, considerando a irradiação dos volumes alvo (PTV) e dos órgãos de risco (OAR). Metodologia – Selecionaram-se 7 pacientes com indicação para RT de mama esquerda. Sobre tomografia computorizada foram feitos os contornos do PTV e dos OAR. Foram calculadas 4 planimetrias/paciente para as TI: conformacional externa (EBRT), intensidade modulada com 2 (IMRT2) e 5 campos (IMRT5) e arco dinâmico (DART). Resultados – Histogramas de dose volume foram comparados para todas as TI usando o software de análise estatística, IBM SPSS v20. Com IMRT5 e DART, os OAR recebem mais doses baixas. No entanto, IMRT5 apresenta melhores índices de conformidade e homogeneidade para o PTV. Conclusões – IMRT5 apresenta o melhor índice de conformidade; EBRT e IMRT2 apresentam melhores resultados que DART. Há d.e.s entre as TI, sobretudo em doses mais baixas nos OAR.

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OBJECTIVE: To analyze the prevalence of physiotherapy utilization and to explore the variables associated to its utilization. METHODS: A population-based cross-sectional study, including 3,100 subjects aged 20 years or more living in the urban area of Pelotas, southern Brazil, was carried out. The sample was selected following a multiple-stage protocol; the census tracts delimited by the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics) were the primary sample units. Following descriptive and crude analyses, Poisson regression models taking the clustering of the sample into account were carried out. Data were collected through face-to-face interviews using a standardized and pre-tested questionnaire. RESULTS: The lifetime utilization of physiotherapy was 30.2%; and physiotherapy utilization in the 12 months prior to the interview was reported by 4.9%. Women, elderly subjects, and those from higher socioeconomic levels were more likely to use physiotherapy. Restricting analysis to subjects who attended physiotherapy, 66% used public health services, 25% used insurance health services and 9% had private sessions. CONCLUSIONS: This is the first population-based study on physiotherapy utilization carried out in Brazil. Utilization of physio therapy was lower than reported in both developed and developing countries. The study findings might help public health authorities to organize healthcare service in terms of this important demand.

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Copyright © 2013 Springer Netherlands.

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Copyright © 2013 Springer Netherlands.

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Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases. This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions. The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.

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V Congreso de Eficiencia y Productividad EFIUCO, Córdoba, 19-20 Mayo 2011.

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OBJETIVO: Identificar os determinantes da desnutrição energético-protéica que ocasionam déficits ponderal e de crescimento linear em crianças. MÉTODOS: Estudo transversal envolvendo 1.041 crianças (menores de dois anos de idade) de 10 municípios do Estado da Bahia, de 1999 a 2000. Utilizou-se a técnica de regressão logística e estratégia da abordagem hierárquica para identificar os fatores associados ao estado antropométrico. RESULTADOS: O modelo final para déficit no crescimento linear revelou como determinante básico: a posse de dois ou menos equipamentos domésticos (OR=2,9; IC 95%: 1,74-4,90) e no nível subjacente, a ausência de consulta pré-natal (OR=2,7; IC 95%: 1,47-4,97); entre os determinantes imediatos o baixo peso ao nascer (<2.500 g) (OR=3,6; IC 95%: 1,72-7,70) e relato de hospitalização nos 12 meses anteriores à entrevista (OR=2,4; IC 95%: 1,42-4,10). Fatores determinantes no déficit ponderal nos níveis básico, subjacente e imediato foram, respectivamente: a renda mensal per capita inferior a ¼ do salário-mínimo (OR=3,4; IC 95%: 1,41-8,16), a ausência de pré-natal (OR=2,1; IC 95%: 1,03-4,35), e o baixo peso ao nascer (OR=4,8; IC 95%: 2,00-11,48). CONCLUSÕES: Os déficits ponderal e linear das crianças foram explicados pela intermediação entre as precárias condições materiais de vida e o restrito acesso ao cuidado com a saúde e a carga de morbidade. Intervenções que melhorem as condições de vida e ampliem o acesso às ações do serviço de saúde são estratégias que caminham na busca da eqüidade em saúde e nutrição na infância.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)