Process / pipelineSimulation / optimization
贝叶斯蚁群优化 — 具有贝叶斯概率参数学习的ACO
贝叶斯蚁群优化（BACO）是一种混合元启发式算法，它将贝叶斯推理嵌入蚁群优化框架中。通过将信息素强度或算法参数视为概率分布并用收集到的证据进行更新，BACO在嘈杂或不确定的组合优化问题上比经典ACO具有更高的收敛可靠性和鲁棒性。
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来源
- Dorigo, M., Maniezzo, V., Colorni, A. (1996). Ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 26(1), 29–41. DOI: 10.1109/3477.484436 ↗
- Ant colony optimization algorithms. Wikipedia. link ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Ant Colony Optimization — ACO with Bayesian probabilistic parameter learning. ScholarGate. https://scholargate.app/zh/simulation/bayesian-ant-colony-optimization
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