विधियों की तुलना करें

	फायरफ्लाई एल्गोरिथम	कुक्कुट खोज
क्षेत्र	अनुकूलन	अनुकूलन
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2008	2009
प्रवर्तक	Xin-She Yang	—
प्रकार	Swarm intelligence metaheuristic	Population-based metaheuristic / swarm intelligence
मौलिक स्रोत	Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84.	Yang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE.
उपनाम	FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)	Guguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy Flights
संबंधित	5	6
सारांश	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.	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.