Process / pipelineSimulation / optimization
贝叶斯混合整数规划 — 混合整数搜索空间上的代理辅助优化
贝叶斯混合整数规划（BO-MIP）将概率代理模型（通常是高斯过程）与混合整数规划求解器相结合，以有效地优化在包含连续和离散或整数值决策变量的空间上定义的昂贵黑盒目标函数。当每次函数评估成本高昂且穷举搜索不可行时，它尤其有价值。
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来源
- Baptista, R., Poloczek, M. (2018). Bayesian Optimization of Combinatorial Structures. Proceedings of the 35th International Conference on Machine Learning (ICML), PMLR 80:462–471. link ↗
- Bonami, P., Biegler, L. T., Conn, A. R., Cornuejols, G., Grossmann, I. E., Laird, C. D., Lee, J., Lodi, A., Margot, F., Sawaya, N., Wächter, A. (2008). An algorithmic framework for convex mixed integer nonlinear programs. Discrete Optimization, 5(2), 186–204. DOI: 10.1016/j.disopt.2006.10.011 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Mixed-Integer Programming — Surrogate-Assisted Optimization over Mixed-Integer Search Spaces. ScholarGate. https://scholargate.app/zh/simulation/bayesian-mixed-integer-programming
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