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Genetisk algoritm×Harmony Search×
ÄmnesområdeOptimeringOptimering
FamiljProcess / pipelineProcess / pipeline
Ursprungsår19752001
UpphovspersonJohn Henry HollandZong Woo Geem, Joong Hoon Kim, G. V. Loganathan
TypPopulation-based metaheuristicMetaheuristic population-based optimization
UrsprungskällaHolland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗
AliasGA, evolutionary algorithm, Genetik Algoritma — Evrimsel OptimizasyonHS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization
Närliggande55
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.Harmony Search (HS) is a population-based metaheuristic optimization algorithm introduced by Geem, Kim, and Loganathan in 2001. It mimics the improvisation process of jazz musicians seeking a perfect state of harmony, using three operators — memory consideration, pitch adjustment, and random selection — to generate candidate solutions. The algorithm applies to both continuous and discrete variables and has found wide use in engineering design, water distribution network optimization, and combinatorial problems.
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ScholarGateJämför metoder: Genetic Algorithm · Harmony Search. Hämtad 2026-06-17 från https://scholargate.app/sv/compare