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ГалузьОптимізаціяОптимізація
РодинаProcess / pipelineProcess / pipeline
Рік появи20092008
Автор методуXin-She Yang
ТипPopulation-based metaheuristic / swarm intelligenceSwarm intelligence metaheuristic
Основоположне джерелоYang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE. link ↗Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗
Інші назвиGuguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy FlightsFA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)
Пов'язані65
ПідсумокCuckoo 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.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.
ScholarGateНабір даних
  1. v1
  2. 2 Джерела
  3. PUBLISHED
  1. v1
  2. 2 Джерела
  3. PUBLISHED

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ScholarGateПорівняння методів: Cuckoo Search · Firefly Algorithm. Отримано 2026-06-15 з https://scholargate.app/uk/compare