Adaptive Evolutionary Algorithm Based on Memory Effect

摘要：

In order to improve the algorithm of adaptive ability, introducing memory ability in evolutionary algorithm framework, a new adaptive evolutionary algorithm based on memory effect (EABME) is proposed. The algorithm set matrix to record the exploring experiences and exploring results of the individual parent. The algorithm uses these records to guide the generation of offspring. And thus you can adaptively select the dimension to mutate and exploring radius. In addition, to improve the algorithm accuracy, the algorithm raises the best opportunities by using super-variation operator. In the simulation test, compared with similar algorithms, the results show that EABME has fast convergence speed and optimum performance of global convergence.

关键词： Evolutionary algorithm Memory effect Super-mutation

作者: SONG Dan XUE Juan LIAO Minhua LIAO Xiaodong

作者单位: Department of Information Management, Hunan University of Finance and Economics,Changsha, China School of Public Administration,Guizhou College of Finance and Economics,Guiyang, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 475-478

在线出版日期: 2011-01-21（万方平台首次上网日期，不代表论文的发表时间）