The Whale Optimization Algorithm

•The Whale Optimization Algorithm inspired by humpback whales is proposed.•The WOA algorithm is benchmarked on 29 well-known test functions.•The results on the unimodal functions show the superior exploitation of WOA.•The exploration ability of WOA is confirmed by the results on multimodal functions...

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Vydáno v:	Advances in engineering software (1992) Ročník 95; s. 51 - 67
Hlavní autoři:	Mirjalili, Seyedali, Lewis, Andrew
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.05.2016
Témata:	Algorithm Algorithms Benchmark Computer programs Constrained optimization Genetic algorithm Heuristic algorithm Heuristic methods Hunting Mathematical analysis Optimization Particle swarm optimization Strategy Structural optimization Whales Structural optimization Heuristic algorithm Genetic algorithm Benchmark Particle swarm optimization Algorithm Optimization Constrained optimization
ISSN:	0965-9978
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	•The Whale Optimization Algorithm inspired by humpback whales is proposed.•The WOA algorithm is benchmarked on 29 well-known test functions.•The results on the unimodal functions show the superior exploitation of WOA.•The exploration ability of WOA is confirmed by the results on multimodal functions.•The results on structural design problems confirm the performance of WOA in practice. This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available at http://www.alimirjalili.com/WOA.html
AbstractList	This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available at http://www.alimirjalili.com/WOA.html •The Whale Optimization Algorithm inspired by humpback whales is proposed.•The WOA algorithm is benchmarked on 29 well-known test functions.•The results on the unimodal functions show the superior exploitation of WOA.•The exploration ability of WOA is confirmed by the results on multimodal functions.•The results on structural design problems confirm the performance of WOA in practice. This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior of humpback whales. The algorithm is inspired by the bubble-net hunting strategy. WOA is tested with 29 mathematical optimization problems and 6 structural design problems. Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods. The source codes of the WOA algorithm are publicly available at http://www.alimirjalili.com/WOA.html
Author	Lewis, Andrew Mirjalili, Seyedali
Author_xml	– sequence: 1 givenname: Seyedali orcidid: 0000-0002-1443-9458 surname: Mirjalili fullname: Mirjalili, Seyedali email: seyedali.mirjalili@griffithuni.edu.au, ali.mirjalili@gmail.com organization: School of Information and Communication Technology, Griffith University, Nathan Campus, Brisbane, QLD 4111, Australia – sequence: 2 givenname: Andrew surname: Lewis fullname: Lewis, Andrew organization: School of Information and Communication Technology, Griffith University, Nathan Campus, Brisbane, QLD 4111, Australia
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Snippet	•The Whale Optimization Algorithm inspired by humpback whales is proposed.•The WOA algorithm is benchmarked on 29 well-known test functions.•The results on the... This paper proposes a novel nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), which mimics the social behavior...
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SubjectTerms	Algorithm Algorithms Benchmark Computer programs Constrained optimization Genetic algorithm Heuristic algorithm Heuristic methods Hunting Mathematical analysis Optimization Particle swarm optimization Strategy Structural optimization Whales
Title	The Whale Optimization Algorithm
URI	https://dx.doi.org/10.1016/j.advengsoft.2016.01.008 https://www.proquest.com/docview/1808079048
Volume	95
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