Process / pipeline
蚁群优化 — 基于群体（Swarm-Based）的组合优化
蚁群优化（Ant Colony Optimization, ACO）是一种元启发式算法，由 Marco Dorigo 及其同事于 20 世纪 90 年代初提出，通过模拟蚂蚁的集体觅食行为来解决组合优化问题。真实蚂蚁会在路径上留下信息素标记，并优先跟随较强的标记；ACO 将这种正反馈机制转化为一种搜索过程，用于寻找图结构问题的优质解，例如旅行商问题、车辆路径规划和调度问题。
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来源
- Dorigo, M. & Gambardella, L.M. (1997). Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation, 1(1), 53-66. DOI: 10.1109/4235.585892 ↗
- Dorigo, M. & Stützle, T. (2004). Ant Colony Optimization. MIT Press. ISBN: 9780262042192
如何引用本页
ScholarGate. (2026, June 1). Ant Colony Optimization (ACO). ScholarGate. https://scholargate.app/zh/optimization/ant-colony-optimization
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