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Genetisk algoritm×Tabu Search×
ÄmnesområdeOptimeringOptimering
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19751989
UpphovspersonJohn Henry HollandFred Glover
TypPopulation-based metaheuristicLocal-search metaheuristic
UrsprungskällaHolland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206. link ↗
AliasGA, evolutionary algorithm, Genetik Algoritma — Evrimsel OptimizasyonTabu Araması (Tabu Search), TS, tabu metaheuristic
Närliggande54
SammanfattningA 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.Tabu Search is a local-search metaheuristic introduced by Fred Glover in 1989 that uses a tabu list — a short-term memory of recently visited solutions — to prevent cycling and escape local optima. By explicitly forbidding moves that reverse recent decisions, the algorithm explores the search space more broadly and, through long-term memory structures such as aspiration criteria, aims to approach the global optimum even in large, complex combinatorial problems.
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ScholarGateJämför metoder: Genetic Algorithm · Tabu Search. Hämtad 2026-06-17 från https://scholargate.app/sv/compare