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Simulated Annealing×Algoritma Genetik×
BidangPengoptimumanPengoptimuman
KeluargaProcess / pipelineProcess / pipeline
Tahun asal19831975
PengasasJohn Henry Holland
JenisProbabilistic metaheuristic / local searchPopulation-based metaheuristic
Sumber perintisKirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗
AliasBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local searchGA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
Berkaitan55
RingkasanSimulated 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.
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ScholarGateBandingkan kaedah: Simulated Annealing · Genetic Algorithm. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare