Research on differential evolution algorithm with dynamic stochastic selection strategy
Taoshen Li · Journal of Guangxi University · 2010
It is a key problem to balance searching for feasible and infeasible areas efficiently.In order to effectively locate the feasible global optimum of evolution algorithm,this paper analyzes how to treat the promising infeasible solutions investigated.Through analyzing the influence of the comparison probability in stochastic ranking on the final position of the feasible solution,a novel dynamic stochastic selection strategy is proposed,and related algorithm implementation within the framework of multimember differential evolution is also discussed.Experimental results on common bench mark functions demonstrate the effectiveness of the strategy.