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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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 583; S. 127601
Hauptverfasser:	Li, Han, Fang, Zheng, Hu, Liwei, Liu, Haonan, Wu, Peishu, Zeng, Nianyin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 28.05.2024
Schlagworte:	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
Online-Zugang:	Volltext
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