839 resultados para Simplex. CPLEXR. Parallel Efficiency. Parallel Scalability. Linear Programming
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This paper presents an algorithm to solve the network transmission system expansion planning problem using the DC model which is a mixed non-linear integer programming problem. The major feature of this work is the use of a Branch-and-Bound (B&B) algorithm to directly solve mixed non-linear integer problems. An efficient interior point method is used to solve the non-linear programming problem at each node of the B&B tree. Tests with several known systems are presented to illustrate the performance of the proposed method. ©2007 IEEE.
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This paper presents a methodology and a mathematical model to solve the expansion planning problem that takes into account the effect of contingencies in the planning stage, and considers the demand as a stochastic variable within a specified range. In this way, it is possible to find a solution that minimizes the investment costs guarantying reliability and minimizing future load shedding. The mathematical model of the expansion planning can be represented by a mixed integer nonlinear programming problem. To solve this problem a specialized Genetic Algorithm combined with Linear Programming was implemented.
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This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.
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This paper presents a new methodology for solving the optimal VAr planning problem in multi-area electric power systems, using the Dantzig-Wolfe decomposition. The original multi-area problem is decomposed into subproblems (one for each area) and a master problem (coordinator). The solution of the VAr planning problem in each area is based on the application of successive linear programming, and the coordination scheme is based on the reactive power marginal costs in the border bus. The aim of the model is to provide coordinated mechanisms to carry out the VAr planning studies maximizing autonomy and confidentiality for each area, assuring global economy to the whole system. Using the mathematical model and computational implementation of the proposed methodology, numerical results are presented for two interconnected systems, each of them composed of three equal subsystems formed by IEEE30 and IEEE118 test systems. © 2011 IEEE.
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The aim of this work is the application of the Interior Point and Branch and Bound methods in multiobjective optimization models related to sugarcane harvest residual biomass. These methods showed their viability to help on choosing the sugarcane planting varieties, searching to optimize cost and energy balance of harvest residual biomass, which have conflitant objectives. These methods provide satisfactory results, with fair computing performance and reliable and consistent solutions to the analyzed models. © 2011 IEEE.
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In trickle irrigation systems, the design is based on the pre-established emission uniformity (EU) which is the combined result of the equipment characteristics and its hydraulic configuration. However, this desired value of the EU may not be confirmed by the final project (in field conditions) and neither by the yield uniformity. The hypotheses of this research were: a) the EU of a trickle irrigation system at field conditions is equal to the emission uniformity pre-established in the its design; b) EU has always the lowest value when compared with other indicators of uniformity; c) the discharge variation coefficient (VC) is not equal to production variation coefficient in the operational unit; d) the difference between the discharge variation coefficient and the productivity variation coefficient depends on the water depth applied. This study aimed to evaluate the relationship between EU used in the irrigation system design and the final yield uniformity. The uniformity indicators evaluated were: EU, distribution uniformity (UD) and the index proposed by Barragan & Wu (2005). They were compared estimating the performance of a trickle irrigation system applied in a citrus orchard with dimensions of 400m x 600m. The design of the irrigation system was optimized by a Linear Programming model. The tree rows were leveled in the larger direction and the spacing adopted in the orchard was 7m x 4m. The manifold line was always operating on a slope condition. The sensitivity analysis involved different slopes, 0, 3, 6, 9 and 12%, and different values of emission uniformity, 60, 70, 75, 80, 85, 90 and 94%. The citrus yield uniformity was evaluated by the variation coefficient. The emission uniformity (EU) after design differed from the EU pre-established, more sharply in the initial values lower than 90%. Comparing the uniformity indexes, the EU always generated lower values when compared with the UD and with the index proposed by Barragan. The emitter variation coefficient was always lower than the productivity variation coefficient. To obtain uniformity of production, it is necessary to consider the irrigation system uniformity and mainly the water depth to be applied.
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The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model; (b) an efficient computational behavior with exiting MILP solvers; and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. © 2012 Published by Elsevier B.V. All rights reserved.
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Perhaps due to its origins in a production scheduling software called Optimised Production Technology (OPT), plus the idea of focusing on system constraints, many believe that the Theory of Constraints (TOC) has a vocation for optimal solutions. Those who assess TOC according to this perspective indicate that it guarantees an optimal solution only in certain circumstances. In opposition to this view and founded on a numeric example of a production mix problem, this paper shows, by means of TOC assumptions, why the TOC should not be compared to methods intended to seek optimal or the best solutions, but rather sufficiently good solutions, possible in non-deterministic environments. Moreover, we extend the range of relevant literature on product mix decision by introducing a heuristic based on the uniquely identified work that aims at achieving feasible solutions according to the TOC point of view. The heuristic proposed is tested on 100 production mix problems and the results are compared with the responses obtained with the use of Integer Linear Programming. The results show that the heuristic gives good results on average, but performance falls sharply in some situations. © 2013 Copyright Taylor and Francis Group, LLC.
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Defining product mix is very important for organisations because it determines how productive resources are allocated among various operations. However, it is often defined subjectively. The methods commonly used for this definition are Integer Linear Programming and heuristics based in Theory of Constraints, which use maximum throughput as a performance measure. Although this measure provides maximum throughput to specific problem, it does not consider aspects of time, as days, utilised to make the throughput. Taking this into account, the aim of this paper is to present a throughput per day approach to define product mix, as well as to propose a constructive heuristic to help in this process. The results show that the proposed heuristic obtained satisfactory approximation when compared to the optimum values obtained by enumeration. © 2013 Copyright Taylor and Francis Group, LLC.
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In this paper, capacitated lot sizing problems in which the classical lot sizing decisions are made considering the transportation costs of the manufactured products were studied. These costs are related to the necessary number of pallets or trucks to pack and/or transport the products from the factory to the warehouse. Three extensions of a mixed integer linear programming model from the literature are considered, representing general cases that are commonly found in companies. These models are tested and evaluated using an optimization package, and a Lagrangian heuristic was developed for one of the extensions proposed.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Engenharia Elétrica - FEIS