文献类型：会议论文

英文题名：Application of chaotic theory in differential evolution algorithms

作者：Yu, Guoyan[1]; Wang, Xiaozhen[2]; Li, Peng[1]

机构：[1] Engineering College, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China; [2] Information College, Guangdong Ocean University, Zhanjiang, Guangdong 524088, China

会议论文集：Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010

会议日期：10 August 2010 through 12 August 2010

会议地点：Yantai, Shandong

语种：英文

外文关键词：Multiobjective optimization

外文摘要：Previous researches have shown that hybrid differential evolution (DE) algorithms incorporated with chaotic sequences are effective in solving single objective optimization problem. Based on these pioneering efforts, this paper extends the hybrid chaotic DE to solve multi-objective optimization problems (MOPs). First, various application of chaotic sequence in DE are studied in detail, and different hybrid chaotic DE algorithms are compared and analyzed in order to find one general chaotic DE. Then, the performances and effectiveness of various hybrid chaotic DE algorithms existed in related literature are examined based upon five benchmark constraint MOPs. The comparative study shows that the hybrid DE with chaotic migration outperformed the hybrid DE with chaotic self-adaptive control parameters F and CR setting. The results also demonstrated that the hybrid chaotic DE is not effective for solving MOPs, while it is successful and competitive for solving single objective optimization problem. ?2010 IEEE.