RESEARCH ON MUTATION OPERATOR OF DIPLOID GENETIC ALGORITHM AND ITS DYNAMIC ADAPTATION STRATEGY
Diploid genetic algorithm (DGA) is a double gene model for the genetic algorithm. This paper theoretically analyses influence of mutation operator on population diversity by introducing an average schema similar rate as the measure criteria of population diversity in DGA. A conclusion is drawn that DGA has a better performance in terms of preserving the diversity than HGA. Furthermore, a dynamic adaptation strategy is proposed to regulate the mutation operator by Mexican hat wavelet along with iterative generations. A simple optimal problem has been chosen to test and simulate on Matlab. Results show that the dynamic adaptation strategy has a better performance in terms of solution accuracy and convergence speed. The simulation results are found to be satisfactory.
Double gene mutation operator dynamic adaptation strategy
LI HE YONG-GANG WU
College of Hydropower & Information Engineering, Huazhong University of Science and Technology,Wuhan, 430074,China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2117-2122
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）