MMODE:A Memetic Multiobjective Differential Evolution Algorithm

摘要：

　　For the multiobjective problems, some global search meth ods may fail to find the Pareto optima with both accuracy and diversity.To pursue the two goals at the same time, a new memetic multiobjective differential evolution algorithm (MMODE) is proposed to hybridize the local search with differential evolution (DE) algorithm.The local search is conducted in an independent population to accelerate the search pro cess, while DE can maintain the diversity.In MMODE, we use a new multiobjective Pareto differential evolution (MOPDE).Experimental re sults show that the MMODE performs better than other two MODEs in respects of the accuracy and diversity, especially for the multimodal functions.

关键词： Memetic algorithm multiobjective optimization differential evolution extensive dominance MMODE

作者: Zhou Wu Xiaohua Xia Jiangfeng Zhang

作者单位: Department of Electrical, Electronic and Computer Engineering University of Pretoria, Pretoria, South Africa

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 422-430

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）