Comparer des méthodes

	Recherche Tabou Multi-objectif (RTMO)	Recherche Tabou
Domaine	Simulation	Optimisation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1997	1989
Auteur d'origine	Hansen, M. P.; building on Glover (1989) Tabu Search	Fred Glover
Type	Metaheuristic multi-objective optimization	Local-search metaheuristic
Source fondatrice	Hansen, M. P. (1997). Tabu search for multiobjective optimization: MOTS. Presented at the 13th International Conference on Multiple Criteria Decision Making (MCDM), Cape Town, South Africa.	Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206.
Alias	MOTS, Multi-criteria Tabu Search, Pareto Tabu Search, TSMOO	Tabu Araması (Tabu Search), TS, tabu metaheuristic
Apparentées	5	4
Résumé	Multi-objective Tabu Search (MOTS) is a metaheuristic algorithm that extends the classic Tabu Search framework to simultaneously optimize two or more conflicting objective functions. Instead of a single optimum, it seeks to approximate the Pareto front — the set of solutions where no objective can be improved without worsening another — making it suitable for complex combinatorial and continuous optimization problems in engineering, logistics, and operations research.	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.