เปรียบเทียบวิธี

	Simulated Annealing	Genetic Algorithm
สาขาวิชา	การหาค่าเหมาะที่สุด	การหาค่าเหมาะที่สุด
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1983	1975
ผู้ริเริ่ม	—	John Henry Holland
ประเภท	Probabilistic metaheuristic / local search	Population-based metaheuristic
แหล่งต้นตำรับ	Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
ชื่อเรียกอื่น	Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
ที่เกี่ยวข้อง	5	5
สรุป	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.	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.