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Waloptimierungsalgorithmus (WOA)×Grey Wolf Optimizer×
FachgebietOptimierungOptimierung
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr20162014
UrheberSeyedali Mirjalili & Andrew LewisSeyedali Mirjalili, Seyed Mohammad Mirjalili, Andrew Lewis
TypSwarm-based metaheuristicSwarm-intelligence metaheuristic
Wegweisende QuelleMirjalili, S. & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. DOI ↗Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey Wolf Optimizer. Advances in Engineering Software, 69, 46-61. DOI ↗
AliasnamenWOA, Balina Optimizasyon Algoritması (WOA), bubble-net attacking methodGWO, Gri Kurt Optimizasyonu, Gri Kurt Optimizasyonu (GWO)
Verwandt55
ZusammenfassungThe Whale Optimization Algorithm (WOA) is a swarm-based metaheuristic introduced by Mirjalili and Lewis in 2016. It models the bubble-net hunting strategy of humpback whales, in which a group of whales spirals around prey while gradually tightening the encirclement. The algorithm balances global exploration and local exploitation through a small set of parameters and has become widely used in continuous engineering optimisation problems.The Grey Wolf Optimizer (GWO) is a swarm-intelligence metaheuristic introduced by Mirjalili, Mirjalili, and Lewis in 2014 that models the social hierarchy and cooperative hunting behaviour of grey wolves. A population of candidate solutions is divided into four leadership ranks — alpha, beta, delta, and omega — and the three best solutions at each iteration guide the entire swarm toward increasingly better regions of the search space.
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ScholarGateMethoden vergleichen: Whale Optimization Algorithm · Grey Wolf Optimizer. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare