Comparar métodos

	Búsqueda Tabú Bayesiana	Búsqueda Tabú Estocástica
Campo	Simulación	Simulación
Familia	Process / pipeline	Process / pipeline
Año de origen	1989 (tabu search); hybrid formulations ~2005–2015	1990s
Autor original	Glover, F. (tabu search); Bayesian integration developed by multiple researchers in the 2000s–2010s	Glover, F. (base TS); stochastic extensions by various authors (1990s–2000s)
Tipo	Hybrid metaheuristic — memory-based local search with Bayesian probabilistic guidance	Stochastic metaheuristic optimizer
Fuente seminal	Glover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206.	Glover, F. (1990). Tabu search: A tutorial. Interfaces, 20(4), 74-94.
Alias	BTS, Bayesian-guided tabu search, probabilistic tabu search, Bayes-TS	STS, Randomized Tabu Search, Probabilistic Tabu Search, Noisy Tabu Search
Relacionados	6	5
Resumen	Bayesian 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.	Stochastic Tabu Search (STS) is an extension of classical Tabu Search that introduces randomness into the neighborhood exploration and move-selection phases. By combining tabu memory — which forbids recently visited solutions — with probabilistic acceptance or random candidate sampling, STS escapes local optima more effectively and explores rugged solution landscapes that deterministic TS may fail to traverse.