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Algorytm świetlików×Harmony Search×
DziedzinaOptymalizacjaOptymalizacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania20082001
TwórcaXin-She YangZong Woo Geem, Joong Hoon Kim, G. V. Loganathan
TypSwarm intelligence metaheuristicMetaheuristic population-based optimization
Źródło pierwotneYang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68. DOI ↗
Inne nazwyFA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)HS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization
Pokrewne55
PodsumowanieThe Firefly Algorithm (FA), introduced by Xin-She Yang in 2008 and formally published in 2010, is a nature-inspired swarm metaheuristic that models the bioluminescent attraction behaviour of fireflies. Each candidate solution is a firefly whose brightness represents its objective-function value; dimmer fireflies move toward brighter ones with an attraction force that decays with distance, driving the swarm toward optima without gradient information.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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ScholarGatePorównaj metody: Firefly Algorithm · Harmony Search. Pobrano 2026-06-17 z https://scholargate.app/pl/compare