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Displaying similar documents to “An interactive fuzzy satisficing method for multiobjective nonlinear integer programming problems with block-angular structures through genetic algorithms with decomposition procedures.”

Extended VIKOR as a new method for solving Multiple Objective Large-Scale Nonlinear Programming problems

Majeed Heydari, Mohammad Kazem Sayadi, Kamran Shahanaghi (2010)

RAIRO - Operations Research

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The VIKOR method was introduced as a Multi-Attribute Decision Making (MADM) method to solve discrete decision-making problems with incommensurable and conflicting criteria. This method focuses on ranking and selecting from a set of alternatives based on the particular measure of “closeness” to the “ideal” solution. The multi-criteria measure for compromise ranking is developed from the – metric used as an aggregating function in a compromise programming method. In this paper, the...

Linear optimization with bipolar max-parametric hamacher fuzzy relation equation constraints

Samaneh Aliannezhadi, Ali Abbasi Molai, Behnaz Hedayatfar (2016)

Kybernetika

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In this paper, the linear programming problem subject to the Bipolar Fuzzy Relation Equation (BFRE) constraints with the max-parametric hamacher composition operators is studied. The structure of its feasible domain is investigated and its feasible solution set determined. Some necessary and sufficient conditions are presented for its solution existence. Then the problem is converted to an equivalent programming problem. Some rules are proposed to reduce the dimensions of problem. Under...

Fuzzy linear programming via simulated annealing

Rita Almeida Ribeiro, Fernando Moura Pires (1999)

Kybernetika

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This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solving fuzzy optimization problems.

Multiobjective De Novo Linear Programming

Petr Fiala (2011)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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Mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives. In multiobjective linear programming problems it is usually impossible to optimize all objectives in a given system. Trade-offs are properties of inadequately designed system a thus can be eliminated through designing better one. Multiobjective De Novo linear programming is problem for designing...