方法证据记录
Robust Mixed-Integer Programming
Robust Mixed-Integer Programming (RMIP) combines mixed-integer programming with robust optimization to find solutions that remain feasible and near-optimal despite uncertain parameters. Instead of assuming fixed data, it protects decisions against adversarial or worst-case realizations of uncertain inputs, using an explicit uncertainty set to control the degree of conservatism while preserving the combinatorial structure of integer decisions.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Mixed-Integer Programming (RMIP) — Optimization under uncertainty with integer decision variables
分类方法记录 · process-pipeline / simulation
- Bertsimas, D., Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35–53. · DOI 10.1287/opre.1030.0065
- Ben-Tal, A., El Ghaoui, L., Nemirovski, A. (2009). Robust Optimization. Princeton University Press, Princeton, NJ. · ISBN 9780691143682
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