Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization

doi:10.1109/JAS.2023.123609

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	Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization
	Wenhua Li; Xingyi Yao; Kaiwen Li; Rui Wang; Tao Zhang; Ling Wang
刊名	IEEE/CAA Journal of Automatica Sinica
	2023
卷号	10 期号:7 页码:1544-1556
关键词	Coevolution ${\bm{\epsilon}}$-dominance generalized multimodal multi-objective optimization (MMO) local convergence two archives
ISSN号	2329-9266
DOI	10.1109/JAS.2023.123609
英文摘要	Most multimodal multi-objective evolutionary algorithms (MMEAs) aim to find all global Pareto optimal sets (PSs) for a multimodal multi-objective optimization problem (MMOP). However, in real-world problems, decision makers (DMs) may be also interested in local PSs. Also, searching for both global and local PSs is more general in view of dealing with MMOPs, which can be seen as generalized MMOPs. Moreover, most state-of-the-art MMEAs exhibit poor convergence on high-dimension MMOPs and are unable to deal with constrained MMOPs. To address the above issues, we present a novel multimodal multi-objective coevolutionary algorithm (CoMMEA) to better produce both global and local PSs, and simultaneously, to improve the convergence performance in dealing with high-dimension MMOPs. Specifically, the CoMMEA introduces two archives to the search process, and coevolves them simultaneously through effective knowledge transfer. The convergence archive assists the CoMMEA to quickly approach the Pareto optimal front. The knowledge of the converged solutions is then transferred to the diversity archive which utilizes the local convergence indicator and the ${\bm{\epsilon}}$-dominance-based method to obtain global and local PSs effectively. Experimental results show that CoMMEA is competitive compared to seven state-of-the-art MMEAs on fifty-four complex MMOPs.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/51992]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Wenhua Li,Xingyi Yao,Kaiwen Li,et al. Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(7):1544-1556.
APA	Wenhua Li,Xingyi Yao,Kaiwen Li,Rui Wang,Tao Zhang,&Ling Wang.(2023).Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization.IEEE/CAA Journal of Automatica Sinica,10(7),1544-1556.
MLA	Wenhua Li,et al."Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization".IEEE/CAA Journal of Automatica Sinica 10.7(2023):1544-1556.