Process / pipelineSimulation / optimization
多目标蚁群优化 (MOACO)
多目标蚁系统优化 (MOACO) 是一种群体智能元启发式算法，它扩展了经典的蚁群优化框架，以同时优化两个或多个相互冲突的目标。人工蚂蚁在信息素轨迹和启发式信息的引导下构建候选解，逐步建立一个帕累托最优解的档案库，而不是收敛到一个单一的最佳答案。
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来源
- Gambardella, L. M., Taillard, E., & Agazzi, G. (1999). MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In D. Corne, M. Dorigo, & F. Glover (Eds.), New Ideas in Optimization (pp. 63–76). McGraw-Hill. link ↗
- Dorigo, M., & Stützle, T. (2004). Ant Colony Optimization. MIT Press. ISBN: 9780262042192
如何引用本页
ScholarGate. (2026, June 3). Multi-Objective Ant Colony Optimization (MOACO). ScholarGate. https://scholargate.app/zh/simulation/multi-objective-ant-colony-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.
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