An Interactive Algorithm for Large Scale Multiple Objective Programming Problems With Fuzzy Parameters Through Topsis Approach
Mahmoud A. Abo-Sinna, Tarek. H. M. Abou-El-Enien (2011)
The Yugoslav Journal of Operations Research
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Mahmoud A. Abo-Sinna, Tarek. H. M. Abou-El-Enien (2011)
The Yugoslav Journal of Operations Research
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José Luis Verdegay, Edmundo Vergara-Moreno (2000)
Mathware and Soft Computing
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Fuzzy rule based termination criteria are introduced in two conventional and exact algorithms solving Knapsack Problems. As a consequence two new solution algorithms are obtained. These algorithms are heuristic ones with a high performance. The efficiency of the algorithms obtained is illustrated by solving some numerical examples.
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.
Shaoyuan Li, Chaofang Hu, Changjun Teng (2004)
Control and Cybernetics
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Sahidul Islam (2010)
The Yugoslav Journal of Operations Research
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Alejandro Sancho-Royo, José Luis Verdegay, Edmundo Vergara-Moreno (1999)
Mathware and Soft Computing
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In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the question, first, of the practical determination of membership functions, second of the management of the fuzziness in some optimisation models, and finally of using fuzzy rules for terminating conventional...
Mariano Jiménez López, María Victoria Rodríguez Uría, María del Mar Arenas Parra, Amelia Bilbao Terol (2000)
Mathware and Soft Computing
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In this paper we propose a method to solve a linear programming problem involving fuzzy parameters whose possibility distributions are given by fuzzy numbers. To address the above problem we have used a preference relationship of fuzzy numbers that leads us to a solving method that produces the so-called α-degree feasible solutions. It must be pointed out that the final solution of the problem depends critically on this degree of feasibility, which is in conflict with the optimal value...
Fang, J., Smith, S.M., Elishakoff, I. (1998)
Mathematical Problems in Engineering
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Karel Zimmermann (2011)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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The aim of this short contribution is to point out some applications of systems of so called two-sided -linear systems of equations and inequalities of [Gavalec, M., Zimmermann, K.: Solving systems of two-sided (max,min)-linear equations Kybernetika 46 (2010), 405–414.] to solving some fuzzy set multiple fuzzy goal problems. The paper describes one approach to formulating and solving multiple fuzzy goal problems. The fuzzy goals are given as fuzzy sets and we look for a fuzzy set, the...
Plamen P. Angelov (1994)
The Yugoslav Journal of Operations Research
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Bogdana Stanojević, Milan Stanojević (2009)
The Yugoslav Journal of Operations Research
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José M. Cadenas, Fernando Jiménez (1996)
Mathware and Soft Computing
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In this paper, we propose a relationship of fuzzy duality. We use the Decomposition Theorem and some properties about Linear Programming with interval coefficients to define this relationship. Thus, a linear programming problem with fuzzy costs represented by membership functions L-R can be solved by means of two dual problems (linear programming problems with fuzzy constraints). Moreover, these results can be applied to multiobjective problems whose coefficients of the objective function...