পদ্ধতির তুলনা করুন

	কাকু অনুসন্ধান	জেনেটিক অ্যালগরিদম
ক্ষেত্র	অনুকূলকরণ	অনুকূলকরণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	2009	1975
প্রবর্তক	—	John Henry Holland
ধরন	Population-based metaheuristic / swarm intelligence	Population-based metaheuristic
মৌলিক উৎস	Yang, X.S. & Deb, S. (2009). Cuckoo Search via Lévy Flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 210-214. IEEE.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
অপর নাম	Guguk Kuşu Araması (Cuckoo Search), CS algorithm, Cuckoo Search via Lévy Flights	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
সম্পর্কিত	6	5
সারসংক্ষেপ	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.	A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.