Set covering-based topsis method for sloving sup-T equation constrained multi-objective optimization problems

Abstract

This paper considers solving a multi-objective optimization problem with sup-T equation constraints. A set covering-based technique for order of preference by similarity to the ideal solution is proposed for solving such a problem. It is shown that a compromise solution of the sup-T equation constrained multi-objective optimization problem can be obtained by solving an associated set covering problem. A surrogate heuristic is then applied to solve the resulting optimization problem. Numerical experiments on solving randomly generated multi-objective optimization problems with sup-T equation constraints are included. Our computational results confirm the efficiency of the proposed method and show its potential for solving large scale sup-T equation constrained multi-objective optimization problems.

Keywords

Fuzzy relational equations / fuzzy optimization / set covering problems

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