Constraint handling technique based on Lebesgue measure for constrained multiobjective particle swarm optimization algorithm

In this paper, we study on how to achieve balance between minimizing the objectives, satisfying the constraints, and avoiding the population to stuck at locally optimal or locally feasible regions. We propose a new constraints handling technique based on diversity distance measure for constrained mu...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Knowledge-based systems Ročník 227; s. 107131
Hlavní autori:	Wang, Hui, Cai, Tie, Li, Kangshun, Pedrycz, Witold
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 05.09.2021 Elsevier Science Ltd
Predmet:	Algorithms Competition Competitiveness Constraints Constraints handle technique based on Lebesgue measure Diversity distance measure Experiments Function words Interactive effects of constraints Mahalanobis distance Modified mechanism of objective space Multiple objective analysis Objectives Optimization Pareto optimization Particle swarm optimization Pull and Push search Regions Diversity distance measure Pull and Push search Modified mechanism of objective space Mahalanobis distance Constraints handle technique based on Lebesgue measure Interactive effects of constraints
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!