An interactive method using genetic algorithm for multi-objective optimization problems modeled in fuzzy environment

摘要: In this paper, an interactive approach based method is proposed for solving multi-objective optimization problems. The can be used to obtain those Pareto-optimal solutions of the mathematical models linear as well nonlinear problems modeled in fuzzy or crisp environment which reasonably meet users aspirations. objectives are treated goals and satisfaction constraints considered at different @a-level sets parameter used. Product operator aggregate membership functions objectives. To initiate algorithm, decision maker has specify his(er) preferences desired values form reference levels space. each iterative phase, a single objective (usually nonconvex) problem solved. It solved using real coded genetic MI-LXPM. Based on its outcomes, option modify, if felt necessary, some all function space before initiating next phase. algorithm stopped where user's aspirations met.