Self-adaptive Differential Evolution Algorithm and Its Application to Complex Optimization Problems
Xiao Wen-xia · Harbin Ligong Daxue xuebao · 2015
When differential evolutionary algorithm is used in solving complex optimization problems,capability of global search is decreased in the later evolution period,and the ability of global search is weakened and algorithm can easily fall into local optimum. In response to these problems,stagnation factor and similarity factor are defined.Scaling factor F is adaptive adjusted according to the stagnation factor. Similarity between individuals is determined by the similarity factor,the gene reconstruction is taken. So that the problem of decrease of population diversity can be alleviated. The improved algorithm is applied to standard test function optimization and vehicle routing problem,the results show that improved differential evolution algorithm has better global search ability. And the algorithm is suitable for solving complex optimization problems.