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

Uloženo v:

Podrobná bibliografie
Vydáno v:	Knowledge-based systems Ročník 227; s. 107131
Hlavní autoři:	Wang, Hui, Cai, Tie, Li, Kangshun, Pedrycz, Witold
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 05.09.2021 Elsevier Science Ltd
Témata:	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 přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!