An improved multi-objective evolutionary algorithm based on environmental and history information

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• 作者：Ziyu Hu^a ; ^b ; ^{whoziyu@163.com}Author Vitae ; Jingming Yang^a ; ^bAuthor Vitae ; Hao Sun^a ; ^bAuthor Vitae ; Lixin Wei^a ; ^bAuthor Vitae ; Zhiwei Zhao^a ; ^cAuthor Vitae
• 关键词：Evolutionary computation ; Multi-objective optimization ; Exploitation and exploration ; Evolutionary algorithm
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：26 January 2017
• 年：2017
• 卷：222
• 期：Complete
• 页码：170-182
• 全文大小：1987 K
• 卷排序：222

文摘

A multi-objective evolutionary algorithm is proposed based on history information and environmental information. The conception of locality and reference front is introduced to improve the diversity. The history information and environmental information are used to generate better offspring. Adaptation mechanism of evolutionary operator is proposed to solve searching issue during different evolutionary stages.