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| Cuckoo Search× | Simulated Annealing× | |
|---|---|---|
| Bidang | Pengoptimuman | Pengoptimuman |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2009 | 1983 |
| Pengasas | — | — |
| Jenis≠ | Population-based metaheuristic / swarm intelligence | Probabilistic metaheuristic / local search |
| Sumber perintis≠ | Yang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE. link ↗ | Kirkpatrick, S., Gelatt, C.D. & Vecchi, M.P. (1983). Optimization by Simulated Annealing. Science, 220(4598), 671-680. DOI ↗ |
| Alias | Guguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy Flights | Benzetimli Tavlama (Simulated Annealing), SA, probabilistic local search |
| Berkaitan≠ | 6 | 5 |
| Ringkasan≠ | 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. | Simulated annealing is a probabilistic local-search metaheuristic introduced by Kirkpatrick, Gelatt, and Vecchi in 1983. It models the physical annealing process in metallurgy — where a material is heated and then slowly cooled to reach a low-energy crystalline state — and uses this analogy to escape local optima in combinatorial and continuous optimization problems. |
| ScholarGateSet data ↗ |
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