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Diferenciálna evolúcia×Algoritmus svetlušiek×
OdborOptimalizáciaOptimalizácia
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19972008
TvorcaRainer Storn & Kenneth PriceXin-She Yang
TypPopulation-based stochastic metaheuristicSwarm intelligence metaheuristic
Pôvodný zdrojStorn, R. & Price, K. (1997). Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, 11(4), 341–359. DOI ↗Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗
Ďalšie názvyDE algorithm, Diferansiyel Evrim (DE), DE optimizationFA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)
Príbuzné55
ZhrnutieDifferential Evolution (DE), introduced by Rainer Storn and Kenneth Price in 1997, is a population-based stochastic optimisation algorithm designed for continuous parameter spaces. It generates candidate solutions by combining vector differences between existing population members, making it a powerful and parameter-lean alternative to Genetic Algorithms and Particle Swarm Optimisation when the search landscape is non-convex, multimodal, or poorly suited to gradient-based methods.The 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.
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ScholarGatePorovnať metódy: Differential Evolution · Firefly Algorithm. Získané 2026-06-17 z https://scholargate.app/sk/compare