A novel adaptive control strategy for decomposition-based multiobjective algorithm

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• 作者：Qiuzhen Lin ^{qiuzhlin@szu.edu.cn} ; Chaoyu Tang ; Yueping Ma ; Zhihua Du ; Jianqiang Li ; Jianyong Chen ; ^{jychen@szu.edu.cn} ; Zhong Ming
• 关键词：Evolutionary algorithm ; Multiobjective optimization ; Adaptive differential evolution ; Decomposition
• 刊名：Computers & Operations Research
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：78
• 期：Complete
• 页码：94-107
• 全文大小：2540 K
• 卷排序：78

文摘

A novel adaptive control strategy is designed for MOEA/D. The parameter settings are adaptively adjusted at different evolutionary stages. The advantages of four classical differential evolution strategies are combined. Our algorithm gives better performance in solving complicated UF test problems.