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Bayesian Tabu Search×Wyżarzanie symulowane×
DziedzinaSymulacjaOptymalizacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1989 (tabu search); hybrid formulations ~2005–20151983
TwórcaGlover, F. (tabu search); Bayesian integration developed by multiple researchers in the 2000s–2010s
TypHybrid metaheuristic — memory-based local search with Bayesian probabilistic guidanceProbabilistic metaheuristic / local search
Źródło pierwotneGlover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206. DOI ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
Inne nazwyBTS, Bayesian-guided tabu search, probabilistic tabu search, Bayes-TSBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Pokrewne65
PodsumowanieBayesian Tabu Search (BTS) is a hybrid metaheuristic that couples the memory-based forbidden-move mechanism of classic Tabu Search with a Bayesian probabilistic model. The Bayesian component learns from past evaluations to score candidate moves, focusing the search on promising regions while the tabu list prevents cycling. This combination reduces wasted function evaluations in expensive combinatorial and continuous optimization 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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  3. PUBLISHED

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ScholarGatePorównaj metody: Bayesian Tabu Search · Simulated Annealing. Pobrano 2026-06-18 z https://scholargate.app/pl/compare