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Harmony Search×Simulated Annealing×
FachgebietOptimierungOptimierung
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr20011983
UrheberZong Woo Geem, Joong Hoon Kim, G. V. Loganathan
TypMetaheuristic population-based optimizationProbabilistic metaheuristic / local search
Wegweisende QuelleGeem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗
AliasnamenHS algorithm, Harmoni Araması (Harmony Search), music-inspired optimizationBenzetimli Tavlama (Simulated Annealing), SA, probabilistic local search
Verwandt55
ZusammenfassungHarmony 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.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.
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ScholarGateMethoden vergleichen: Harmony Search · Simulated Annealing. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare