পদ্ধতির তুলনা করুন

	ভেরিয়েবল নেইবারহুড সার্চ (VNS)	জেনেটিক অ্যালগরিদম
ক্ষেত্র	অনুকূলকরণ	অনুকূলকরণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1997	1975
প্রবর্তক	—	John Henry Holland
ধরন	Metaheuristic — neighborhood-based	Population-based metaheuristic
মৌলিক উৎস	Mladenović, N. & Hansen, P. (1997). Variable Neighborhood Search. Computers & Operations Research, 24(11), 1097–1100.	Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.
অপর নাম	VNS, Değişken Komşuluk Araması (VNS), variable neighbourhood search	GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
সম্পর্কিত	4	5
সারসংক্ষেপ	Variable Neighborhood Search (VNS) is a metaheuristic optimization framework introduced by Mladenović and Hansen in 1997. It escapes local optima by systematically switching among a predefined set of neighborhood structures — first perturbing the current solution (shaking) to reach a different region of the search space, then applying a local search within that region, and finally accepting the new solution only if it improves the incumbent. The method is flexible enough to handle combinatorial problems (routing, scheduling, graph problems) as well as continuous optimization, making it one of the most widely used neighborhood-based metaheuristics in operations research.	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.