Data-driven distributionally robust chance-constrained optimization with Wasserstein metric
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DOI: 10.1007/s10898-020-00966-0
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- Ketkov, Sergey S., 2024. "A study of distributionally robust mixed-integer programming with Wasserstein metric: on the value of incomplete data," European Journal of Operational Research, Elsevier, vol. 313(2), pages 602-615.
- Yue Zhao & Zhi Chen & Zhenzhen Zhang, 2023. "Distributionally Robust Chance-Constrained p -Hub Center Problem," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1361-1382, November.
- Nilay Noyan & Gábor Rudolf & Miguel Lejeune, 2022. "Distributionally Robust Optimization Under a Decision-Dependent Ambiguity Set with Applications to Machine Scheduling and Humanitarian Logistics," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 729-751, March.
- van der Laan, Niels & Teunter, Ruud H. & Romeijnders, Ward & Kilic, Onur A., 2022. "The data-driven newsvendor problem: Achieving on-target service-levels using distributionally robust chance-constrained optimization," International Journal of Production Economics, Elsevier, vol. 249(C).
- Zhai, Junyi & Wang, Sheng & Guo, Lei & Jiang, Yuning & Kang, Zhongjian & Jones, Colin N., 2022. "Data-driven distributionally robust joint chance-constrained energy management for multi-energy microgrid," Applied Energy, Elsevier, vol. 326(C).
- Jiang, Jie & Peng, Shen, 2024. "Mathematical programs with distributionally robust chance constraints: Statistical robustness, discretization and reformulation," European Journal of Operational Research, Elsevier, vol. 313(2), pages 616-627.
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Keywords
Distributionally robust optimization; Chance-constrained programming; Wasserstein metric; Mixed-integer programming;All these keywords.
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