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| 다목적 시뮬레이티드 어닐링 (MOSA)× | Multi-objective Tabu Search (MOTS)× | |
|---|---|---|
| 분야 | 시뮬레이션 | 시뮬레이션 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1992–1998 | 1997 |
| 창시자≠ | Serafini, P.; Czyzak, P. and Jaszkiewicz, A. | Hansen, M. P.; building on Glover (1989) Tabu Search |
| 유형≠ | Metaheuristic / Pareto-based optimizer | Metaheuristic multi-objective optimization |
| 원전≠ | 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 ↗ | 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 ↗ |
| 별칭 | MOSA, Multi-Criteria Simulated Annealing, Pareto Simulated Annealing, PSA | MOTS, Multi-criteria Tabu Search, Pareto Tabu Search, TSMOO |
| 관련 | 5 | 5 |
| 요약≠ | 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. | 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. |
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