Abstract To balance the global exploration and local development of differential evolution algorithm(DE) and avoid the algorithm falling into the local optimal, a group mutation adaptive differential evolution algorithm based on probability judgment method(GVADE) is proposed. Evolutionary states of an individual are divided into three states based on probability judgment method: better, worse or general. Then, the appropriate mutation operator and control parameter group are applied for the individual. Meanwhile, a mutation operator with strong global exploratory capability is designed to meet the needs of worse evolutionary individual mutation. The experimental results show that GVADE algorithm is superior to the other DE algorithms on the CEC2005 standard testing sets. It can balance the global exploration and local development well with high convergence accuracy.
Fund:Supported by National Social Science Foundation of China(No.16BTQ084)
About author:: LI Haojun(Corresponding author), Ph.D. candidate, associate professor. His research interests include intelligent computing and mobile learning.LIU Zhongfeng, master student. His research interests include intelligent computing and its application.RAN Jinting, master student. Her research interests include intelligent computing and mobile learning.
LI Haojun,LIU Zhongfeng,RAN Jinting. Group Mutation Adaptive Differential Evolution Algorithm Based on Probability Judgment Method[J]. , 2018, 31(2): 132-141.
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2018, Vol. 31 
