Displaying similar documents to “Solving intuitionistic fuzzy multi-objective linear programming problem and its application in supply chain management”

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.

Interactive decision-making in multiobjetive fuzzy programming.

José M. Cadenas, Fernando Jiménez (1994)

Mathware and Soft Computing

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We present an interactive decision support system which aids in solving a general multiobjective fuzzy problem, that is, a multiobjective programming problem with fuzzy goals subject to a fuzzy constraint set. The interactive decision support system is proposed. After eliciting the fuzzy goals of the decision maker for each objective function and the fuzzy elements for each constraint, the satisfactory solutions for the decision maker were derived by interactively updating the reference...

Solving a possibilistic linear program through compromise programming.

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...

Formal Introduction to Fuzzy Implications

Adam Grabowski (2017)

Formalized Mathematics

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In the article we present in the Mizar system the catalogue of nine basic fuzzy implications, used especially in the theory of fuzzy sets. This work is a continuation of the development of fuzzy sets in Mizar; it could be used to give a variety of more general operations, and also it could be a good starting point towards the formalization of fuzzy logic (together with t-norms and t-conorms, formalized previously).