Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
496926 | Applied Soft Computing | 2011 | 10 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Reza Hassanzadeh, Esmaile Khorram, Iraj Mahdavi, Nezam Mahdavi-Amiri,