Comparar métodos

	Búsqueda de Cucos	Algoritmo de la Luciérnaga
Campo	Optimización	Optimización
Familia	Process / pipeline	Process / pipeline
Año de origen	2009	2008
Autor original	—	Xin-She Yang
Tipo	Population-based metaheuristic / swarm intelligence	Swarm intelligence metaheuristic
Fuente seminal	Yang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE.	Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84.
Alias	Guguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy Flights	FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)
Relacionados	6	5
Resumen	Cuckoo 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.