Process / pipelineSimulation / optimization
多目标粒子群优化 (MOPSO)
多目标粒子群优化 (MOPSO) 是一种群体智能元启发式算法，它扩展了原始的粒子群优化 (PSO) 以同时处理多个相互冲突的目标函数。它维护一个外部帕累托存档，并使用基于支配的选择来引导候选解种群趋向真实的帕累托前沿，而无需先验的偏好信息。
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Method map
The neighbourhood of related methods — select a node to explore.
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来源
- Coello Coello, C. A., Pulido, G. T., & Lechuga, M. S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 256–279. DOI: 10.1109/TEVC.2004.826067 ↗
- Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks (ICNN), Perth, Australia, 4, 1942–1948. DOI: 10.1109/ICNN.1995.488968 ↗
如何引用本页
ScholarGate. (2026, June 3). Multi-Objective Particle Swarm Optimization (MOPSO). ScholarGate. https://scholargate.app/zh/simulation/multi-objective-particle-swarm-optimization
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
- 多目标优化仿真↔ compare
- 多目标模拟退火 (MOSA)仿真↔ compare
- 粒子群优化 (PSO)优化↔ compare