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Cuckoo Search×Ewolucja Różnicowa×
DziedzinaOptymalizacjaOptymalizacja
RodzinaProcess / pipelineProcess / pipeline
Rok powstania20091997
TwórcaRainer Storn & Kenneth Price
TypPopulation-based metaheuristic / swarm intelligencePopulation-based stochastic metaheuristic
Źródło pierwotneYang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE. link ↗Storn, 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 ↗
Inne nazwyGuguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy FlightsDE algorithm, Diferansiyel Evrim (DE), DE optimization
Pokrewne65
PodsumowanieCuckoo Search (CS) is a population-based metaheuristic optimization algorithm introduced by Xin-She Yang and Suash Deb in 2009. It models the obligate brood-parasitism of cuckoo birds — which lay eggs in other birds' nests — combined with Lévy flight random walks that enable long-range exploration of the search space. The algorithm has proven effective in structural engineering design, machine learning hyperparameter tuning, and other continuous black-box optimization problems.Differential 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.
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ScholarGatePorównaj metody: Cuckoo Search · Differential Evolution. Pobrano 2026-06-17 z https://scholargate.app/pl/compare