قارن الطرق

	البحث العشوائي المحظور	الخوارزمية الجينية العشوائية
المجال	المحاكاة	المحاكاة
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	1990s	1975
صاحب الطريقة	Glover, F. (base TS); stochastic extensions by various authors (1990s–2000s)	Holland, J. H.
النوع	Stochastic metaheuristic optimizer	Stochastic evolutionary metaheuristic
المصدر التأسيسي	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, Ann Arbor. ISBN: 978-0262581110
الأسماء البديلة	STS, Randomized Tabu Search, Probabilistic Tabu Search, Noisy Tabu Search	SGA, Canonical Genetic Algorithm, Simple Genetic Algorithm, Evolutionary Algorithm
ذات صلة	5	5
الملخص	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.	The Stochastic Genetic Algorithm (SGA) is a population-based metaheuristic that mimics biological evolution — selection, crossover, and mutation — to search for near-optimal solutions in complex, nonlinear, or combinatorial spaces. Its randomized operators make it robust to local optima and broadly applicable across engineering, scheduling, machine learning, and operations research.