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...

Celý popis

Podrobná bibliografia

Vydané v:	Neurocomputing (Amsterdam) Ročník 583; s. 127601
Hlavní autori:	Li, Han, Fang, Zheng, Hu, Liwei, Liu, Haonan, Wu, Peishu, Zeng, Nianyin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 28.05.2024
Predmet:	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 prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!