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Multi-objective Tabu Search (MOTS)×Tabu Search×
분야시뮬레이션최적화
계열Process / pipelineProcess / pipeline
기원 연도19971989
창시자Hansen, M. P.; building on Glover (1989) Tabu SearchFred Glover
유형Metaheuristic multi-objective optimizationLocal-search metaheuristic
원전Hansen, 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. link ↗Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206. link ↗
별칭MOTS, Multi-criteria Tabu Search, Pareto Tabu Search, TSMOOTabu Araması (Tabu Search), TS, tabu metaheuristic
관련54
요약Multi-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.
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