Hybrid Fuzzymulti-objectiveevolutionary Algorithm: a Novel Pareto-optimization Technique
نویسندگان
چکیده
A novel pareto-optimization technique based on newly developed hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) is presented in this paper. In HFMOEA, two significant parameters such as crossover probability (PC) and mutation probability (PM) are dynamically varied during optimization based on the output of a fuzzy controller for improving its convergence performance by guiding the direction of stochastic search to reach near the true pareto-optimal solution effectively. The performance of HFMOEA is tested on three benchmark test problems such as ZDT1, ZDT2 and ZDT3 and compared with NSGA-II.
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تاریخ انتشار 2012