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| Cuckoo Search× | Algorytm świetlików× | |
|---|---|---|
| Dziedzina | Optymalizacja | Optymalizacja |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 2009 | 2008 |
| Twórca≠ | — | Xin-She Yang |
| Typ≠ | Population-based metaheuristic / swarm intelligence | Swarm intelligence metaheuristic |
| Źródło pierwotne≠ | Yang, 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 ↗ |
| Inne nazwy | Guguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy Flights | FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm) |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | 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. |
| ScholarGateZbiór danych ↗ |
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