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...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 227; p. 107131
Main Authors:	Wang, Hui, Cai, Tie, Li, Kangshun, Pedrycz, Witold
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 05.09.2021 Elsevier Science Ltd
Subjects:	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
Online Access:	Get full text
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