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حوزهبهینه‌سازیبهینه‌سازی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19751983
پدیدآورJohn Henry Holland
نوعPopulation-based metaheuristicProbabilistic metaheuristic / local search
منبع بنیادینHolland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
نام‌های دیگرGA, evolutionary algorithm, Genetik Algoritma — Evrimsel OptimizasyonBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
مرتبط55
خلاصهA 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.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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ScholarGateمقایسهٔ روش‌ها: Genetic Algorithm · Simulated Annealing. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare