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Algoritmus optimalizace velryb (WOA)×Simulated Annealing×
OborOptimalizaceOptimalizace
RodinaProcess / pipelineProcess / pipeline
Rok vzniku20161983
TvůrceSeyedali Mirjalili & Andrew Lewis
TypSwarm-based metaheuristicProbabilistic metaheuristic / local search
Původní zdrojMirjalili, S. & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. DOI ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
Další názvyWOA, Balina Optimizasyon Algoritması (WOA), bubble-net attacking methodBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Příbuzné55
ShrnutíThe 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.Simulated annealing is a probabilistic local-search metaheuristic introduced by Kirkpatrick, Gelatt, and Vecchi in 1983. It models the physical annealing process in metallurgy — where a material is heated and then slowly cooled to reach a low-energy crystalline state — and uses this analogy to escape local optima in combinatorial and continuous optimization problems.
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ScholarGatePorovnat metody: Whale Optimization Algorithm · Simulated Annealing. Získáno 2026-06-17 z https://scholargate.app/cs/compare