Even Search in a Promising Region for Constrained Multi-Objective Optimization

doi:10.1109/JAS.2023.123792

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	Even Search in a Promising Region for Constrained Multi-Objective Optimization
	Fei Ming; Wenyin Gong; Yaochu Jin
刊名	IEEE/CAA Journal of Automatica Sinica
	2024
卷号	11 期号:2 页码:474-486
关键词	Constrained multi-objective optimization even search evolutionary algorithms promising region real-world problems
ISSN号	2329-9266
DOI	10.1109/JAS.2023.123792
英文摘要	In recent years, a large number of approaches to constrained multi-objective optimization problems (CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However, an overly fine-tuned strategy or technique might overfit some problem types, resulting in a lack of versatility. In this article, we propose a generic search strategy that performs an even search in a promising region. The promising region, determined by obtained feasible non-dominated solutions, possesses two general properties. First, the constrained Pareto front (CPF) is included in the promising region. Second, as the number of feasible solutions increases or the convergence performance (i.e., approximation to the CPF) of these solutions improves, the promising region shrinks. Then we develop a new strategy named even search, which utilizes the non-dominated solutions to accelerate convergence and escape from local optima, and the feasible solutions under a constraint relaxation condition to exploit and detect feasible regions. Finally, a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region. Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promising region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54556]
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	Fei Ming,Wenyin Gong,Yaochu Jin. Even Search in a Promising Region for Constrained Multi-Objective Optimization[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(2):474-486.
APA	Fei Ming,Wenyin Gong,&Yaochu Jin.(2024).Even Search in a Promising Region for Constrained Multi-Objective Optimization.IEEE/CAA Journal of Automatica Sinica,11(2),474-486.
MLA	Fei Ming,et al."Even Search in a Promising Region for Constrained Multi-Objective Optimization".IEEE/CAA Journal of Automatica Sinica 11.2(2024):474-486.