Compară metode

	Căutare cu Vecinătăți Variabile (VNS)	Harmony Search	Metaeuristică de Căutare Locală
Domeniu	Optimizare	Optimizare	Optimizare
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Anul apariției	1997	2001	1989
Autorul original	—	Zong Woo Geem, Joong Hoon Kim, G. V. Loganathan	Fred Glover
Tip	Metaheuristic — neighborhood-based	Metaheuristic population-based optimization	Local-search metaheuristic
Sursa seminală	Mladenović, N. & Hansen, P. (1997). Variable Neighborhood Search. Computers & Operations Research, 24(11), 1097–1100.	Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60–68.	Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206.
Denumiri alternative	VNS, Değişken Komşuluk Araması (VNS), variable neighbourhood search	HS algorithm, Harmoni Araması (Harmony Search), music-inspired optimization	Tabu Araması (Tabu Search), TS, tabu metaheuristic
Înrudite	4	5	4
Rezumat	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.	Harmony Search (HS) is a population-based metaheuristic optimization algorithm introduced by Geem, Kim, and Loganathan in 2001. It mimics the improvisation process of jazz musicians seeking a perfect state of harmony, using three operators — memory consideration, pitch adjustment, and random selection — to generate candidate solutions. The algorithm applies to both continuous and discrete variables and has found wide use in engineering design, water distribution network optimization, and combinatorial problems.	Tabu Search is a local-search metaheuristic introduced by Fred Glover in 1989 that uses a tabu list — a short-term memory of recently visited solutions — to prevent cycling and escape local optima. By explicitly forbidding moves that reverse recent decisions, the algorithm explores the search space more broadly and, through long-term memory structures such as aspiration criteria, aims to approach the global optimum even in large, complex combinatorial problems.