方法证据记录
Bayesian Tabu Search
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Tabu Search — Probabilistic guidance integrated with memory-based local search
分类方法记录 · process-pipeline / simulation
- Glover, F. (1989). Tabu search — Part I. ORSA Journal on Computing, 1(3), 190–206. · DOI 10.1287/ijoc.1.3.190
- Bergstra, J., Bardenet, R., Bengio, Y., Kegl, B. (2011). Algorithms for hyper-parameter optimization. Advances in Neural Information Processing Systems (NIPS), 24, 2546–2554. · URL
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