A novel Whale Optimization Algorithm integrated with Nelder–Mead simplex for multi-objective optimization problems

Recently, several meta-heuristics and evolutionary algorithms have been proposed for tackling optimization problems. Such methods tend to suffer from degraded performance when solving multi-objective optimization problems due to addressing the conflicting goals of finding accurate estimation of Pare...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 212; p. 106619
Main Authors:	Abdel-Basset, Mohamed, Mohamed, Reda, Mirjalili, Seyedali
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 05.01.2021 Elsevier Science Ltd
Subjects:	Algorithm Algorithms Artificial Intelligence Convergence Dynamic distance Evolutionary algorithms Experiments Heuristic Multi-objective optimization Multiple objective analysis Nelder–Mead method Novels Objectives Opposition based learning Optimization Optimization algorithms Pareto optimization Pareto optimum Performance degradation Swarm Intelligence Tests Whale Optimization Algorithm Whales & whaling WOA Nelder–Mead method Whale Optimization Algorithm Artificial Intelligence WOA Multi-objective optimization Dynamic distance Algorithm Opposition based learning Optimization Swarm Intelligence
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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