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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Veröffentlicht in:	Knowledge-based systems Jg. 212; S. 106619
Hauptverfasser:	Abdel-Basset, Mohamed, Mohamed, Reda, Mirjalili, Seyedali
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 05.01.2021 Elsevier Science Ltd
Schlagworte:	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-Zugang:	Volltext
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