ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Annealing Simulat×Algorisme genètic×
CampOptimitzacióOptimització
FamíliaProcess / pipelineProcess / pipeline
Any d'origen19831975
Autor originalJohn Henry Holland
TipusProbabilistic metaheuristic / local searchPopulation-based metaheuristic
Font seminalKirkpatrick, 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 ↗
ÀliesBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local searchGA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
Relacionats55
ResumSimulated 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.
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 2 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: Simulated Annealing · Genetic Algorithm. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare