A novel population robustness-based switching response framework for solving dynamic multi-objective problems

In this paper, a novel population robustness-based switching response framework (PR-SRF) is proposed to develop effective dynamic multi-objective optimization algorithm (DMOA), which integrates different response strategies to comprehensively cope with the dynamic behaviors. In particular, the popul...

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Vydáno v:	Neurocomputing (Amsterdam) Ročník 583; s. 127601
Hlavní autoři:	Li, Han, Fang, Zheng, Hu, Liwei, Liu, Haonan, Wu, Peishu, Zeng, Nianyin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 28.05.2024
Témata:	Dynamic multi-objective optimization algorithms (DMOAs) Evolutionary transfer optimization (ETO) Population robustness Switching response framework Evolutionary transfer optimization (ETO) Switching response framework Population robustness Dynamic multi-objective optimization algorithms (DMOAs)
ISSN:	0925-2312, 1872-8286
On-line přístup:	Získat plný text
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