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| Multi-objective Tabu Search (MOTS)× | 다목적 시뮬레이티드 어닐링 (MOSA)× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1997 | 1992–1998 |
| 창시자≠ | Hansen, M. P.; building on Glover (1989) Tabu Search | Serafini, P.; Czyzak, P. and Jaszkiewicz, A. |
| 유형≠ | Metaheuristic multi-objective optimization | Metaheuristic / Pareto-based optimizer |
| 원전≠ | 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. link ↗ | Czyzak, P., Jaszkiewicz, A. (1998). Pareto simulated annealing — a metaheuristic technique for multiple-objective combinatorial optimization. Journal of Multi-Criteria Decision Analysis, 7(1), 34–47. DOI ↗ |
| 별칭 | MOTS, Multi-criteria Tabu Search, Pareto Tabu Search, TSMOO | MOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSA |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Multi-Objective Simulated Annealing (MOSA) extends the classical simulated annealing metaheuristic to problems with two or more conflicting objective functions. Instead of converging to a single optimum, MOSA explores the solution space stochastically and maintains an archive of non-dominated (Pareto-optimal) solutions, offering decision-makers a diverse trade-off front rather than one prescribed answer. |
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