Reconfiguração de sistemas de distribuição de energia elétrica utilizando a metaheurística busca em vizinhança variável

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento de reativos em sistemas de energia elétrica através de um algoritmo de Branch-and-Bound não linear

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento de redes de distribuição de energia elétrica de média e baixa tensão

Pós-graduação em Engenharia Elétrica - FEIS

Fluxo de potência ótimo em sistemas multimercados através de um algorítmo evolutivo multiobjetivo

Pós-graduação em Engenharia Elétrica - FEIS

Métodos de solução para um problema de sequenciamento da produção com sincronismo de execução de tarefas

Pós-graduação em Engenharia Mecânica - FEG

Modelagem generalizada do problema de planejamento da expansão de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Saddle Point and Second Order Optimality in Nondifferentiable Nonlinear Abstract Multiobjective Optimization

This article deals with a vector optimization problem with cone constraints in a Banach space setting. By making use of a real-valued Lagrangian and the concept of generalized subconvex-like functions, weakly efficient solutions are characterized through saddle point type conditions. The results, jointly with the notion of generalized Hessian (introduced in [Cominetti, R., Correa, R.: A generalized second-order derivative in nonsmooth optimization. SIAM J. Control Optim. 28, 789–809 (1990)]), are applied to achieve second order necessary and sufficient optimality conditions (without requiring twice differentiability for the objective and constraining functions) for the particular case when the functionals involved are defined on a general Banach space into finite dimensional ones.

Localização e preço de contrato ótimo da geração distribuída em sistemas de distribuição radiais de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Planejamento de reativos em sistemas elétricos de potência multi-área através de modelos estocásticos

Pós-graduação em Engenharia Elétrica - FEIS

Algoritmo tabu search especializado para o problema de planejamento da expansao de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

Reactive power planning under conditional-value-at-risk assessment using chance-constrained optimisation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Accuracy of nonlinear feed formulation for broiler chickens: maximising broiler profit

The modeling technique is simple, useful and practical to calculate optimum nutrient density to maximize profit margins, using nonlinear programming by predictive broiler performance. To demonstrate the influence of the broiler price could interact with nutrient density, the experiment aimed to define the quadratic equations for consumption and weight gain, based on modeling, to be applied to nonlinear programming, according to sex (male and female) in the starter (1 to 21 days), grower (22 to 42 days) and finisher phases (43 to 56 days). The experimental design was a randomized, totaling 6 treatments [energy levels of 2800, 2900, 3000, 3100, 3200 and 3300kcal AME/kg with constant nutrient : AME (Apparent Metabolizable Energy)] with 4 replicates and 10 birds per plot, using the program free download PPFR Excel workbook for feed formulation (http://www.foa.unesp.br/downloads/file_detalhes.asp?CatCod=4&SubCatCod=138&FileCod=1677). Data from this trial confirmed that there was a significant relationship between feed intake and total energy consumption of the diet, in which feed intake was increased or decreased simply to keep the amount of energy, with a constant rate of nutrient : AME. Therefore, the data support that if the essential dietary nutrients are kept in proportion to the energy density of the diet, according to the appropriate requirements (male / female) of broilers, the weight and feed conversion are significantly (P<0.05) favored by increasing the energy density of the diet. Thus, it enables the application of models for maximum profit (nonlinear formulation), to estimate the proportion of weight gain most appropriate according to the price paid by the market.

Integrated pulp and paper mill planning and scheduling

This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations. (C) 2012 Elsevier Ltd. All rights reserved.

Asynchronous teams for joint lot-sizing and scheduling problem in flow shops

The integrated production scheduling and lot-sizing problem in a flow shop environment consists of establishing production lot sizes and allocating machines to process them within a planning horizon in a production line with machines arranged in series. The problem considers that demands must be met without backlogging, the capacity of the machines must be respected, and machine setups are sequence-dependent and preserved between periods of the planning horizon. The objective is to determine a production schedule to minimise the setup, production and inventory costs. A mathematical model from the literature is presented, as well as procedures for obtaining feasible solutions. However, some of the procedures have difficulty in obtaining feasible solutions for large-sized problem instances. In addition, we address the problem using different versions of the Asynchronous Team (A-Team) approach. The procedures were compared with literature heuristics based on Mixed Integer Programming. The proposed A-Team procedures outperformed the literature heuristics, especially for large instances. The developed methodologies and the results obtained are presented.

MATHEMATICAL MODELS AND POLYHEDRAL STUDIES FOR INTEGRAL SHEET METAL DESIGN

We deal with the optimization of the production of branched sheet metal products. New forming techniques for sheet metal give rise to a wide variety of possible profiles and possible ways of production. In particular, we show how the problem of producing a given profile geometry can be modeled as a discrete optimization problem. We provide a theoretical analysis of the model in order to improve its solution time. In this context we give the complete convex hull description of some substructures of the underlying polyhedron. Moreover, we introduce a new class of facet-defining inequalities that represent connectivity constraints for the profile and show how these inequalities can be separated in polynomial time. Finally, we present numerical results for various test instances, both real-world and academic examples.