Process / pipelineSimulation / optimization
多目标禁忌搜索 (MOTS) — 帕累托最优解的元启发式算法
多目标禁忌搜索 (MOTS) 是一种元启发式算法，它扩展了经典的禁忌搜索框架，以同时优化两个或更多相互冲突的目标函数。它不寻求单一最优解，而是旨在逼近帕累托前沿——即一组解决方案，其中任何一个目标都无法在不恶化另一个目标的情况下得到改善——这使得它适用于工程、物流和运筹学中复杂的组合和连续优化问题。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- 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 ↗
- Glover, F. (1989). Tabu Search — Part I. ORSA Journal on Computing, 1(3), 190–206. DOI: 10.1287/ijoc.1.3.190 ↗
如何引用本页
ScholarGate. (2026, June 3). Multi-objective Tabu Search (MOTS) — Metaheuristic optimization for multiple conflicting objectives. ScholarGate. https://scholargate.app/zh/simulation/multi-objective-tabu-search
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 多目标蚁群优化 (MOACO)仿真↔ compare
- 多目标遗传算法 (MOGA)仿真↔ compare
- 多目标粒子群优化 (MOPSO)仿真↔ compare
- 多目标模拟退火 (MOSA)仿真↔ compare
- 禁忌搜索优化↔ compare