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Bayesian Simulated Annealing×Simulated Annealing – Probabilistisk Optimering×
ÄmnesområdeSimuleringOptimering
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19841983
UpphovspersonGeman, S. & Geman, D. (Bayesian framing); Kirkpatrick, S. et al. (SA foundation)
TypProbabilistic metaheuristic with Bayesian inferenceProbabilistic metaheuristic / local search
UrsprungskällaKirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. DOI ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
AliasBSA, Bayesian SA, Bayesian Stochastic Annealing, Bayesian Thermodynamic OptimizationBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Närliggande55
SammanfattningBayesian Simulated Annealing (BSA) integrates Bayesian prior knowledge about the objective landscape into the simulated annealing search process. By encoding beliefs about promising regions as prior distributions and updating them as the search progresses, BSA focuses computational effort on high-probability areas of the solution space, accelerating convergence and improving solution quality compared to uninformed SA.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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ScholarGateJämför metoder: Bayesian Simulated Annealing · Simulated Annealing. Hämtad 2026-06-19 från https://scholargate.app/sv/compare