পদ্ধতির তুলনা করুন

	Stochastic Tabu Search	জেনেটিক অ্যালগরিদম
ক্ষেত্র	অনুকরণ	অনুকূলকরণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1990s	1975
প্রবর্তক	Glover, F. (base TS); stochastic extensions by various authors (1990s–2000s)	John Henry Holland
ধরন	Stochastic metaheuristic optimizer	Population-based metaheuristic
মৌলিক উৎস	Glover, F. (1990). Tabu search: A tutorial. Interfaces, 20(4), 74-94.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
অপর নাম	STS, Randomized Tabu Search, Probabilistic Tabu Search, Noisy Tabu Search	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
সম্পর্কিত	5	5
সারসংক্ষেপ	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.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.