White Shark Optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems

This paper presents a novel meta-heuristic algorithm so-called White Shark Optimizer (WSO) to solve optimization problems over a continuous search space. The core ideas and underpinnings of WSO are inspired by the behaviors of great white sharks, including their exceptional senses of hearing and sme...

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Veröffentlicht in:	Knowledge-based systems Jg. 243; S. 108457
Hauptverfasser:	Braik, Malik, Hammouri, Abdelaziz, Atwan, Jaffar, Al-Betar, Mohammed Azmi, Awadallah, Mohammed A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 11.05.2022 Elsevier Science Ltd
Schlagworte:	Algorithms Behavior Convergence Efficacy Evolutionary algorithms Evolutionary computation Exploitation Global local relationship Global optimization Heuristic Heuristic methods Meta-heuristics Nature-inspired algorithms Novels Optimization Reliability Reliability analysis Searching Smell Statistical methods Swarm intelligence Tests White Shark Optimizer World problems Swarm intelligence Nature-inspired algorithms White Shark Optimizer Optimization Evolutionary computation Meta-heuristics
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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