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A genetic algorithm for optimization problems with fuzzy relation constraints using max-product composition
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DOI：10.1016/j.asoc.2009.12.014.png)
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Abstract
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We consider nonlinear optimization problems constrained by a system of fuzzy relation equations. The solution set of the fuzzy relation equations being nonconvex, in general, conventional nonlinear programming methods are not practical. Here, we propose a genetic algorithm with max-product composition to obtain a near optimal solution for convex or nonconvex solution set. Test problems are constructed to evaluate the performance of the proposed algorithm showing alternative solutions obtained by our proposed model. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Fuzzy relation equations
Genetic algorithms
Nonlinear optimization
Max-product composition
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