In this paper, we study a distributionally robust optimization approach to chance-constrained stochastic programs to hedge against uncertainty in the distributions of the random parameters. We consider a general polyhedral ambiguity set under finite support. We develop a decomposition-based solution approac...
Convex semiヾefinite semi﹊nfinite programming problems (SDSIP) represent a special class of distributionally robust optimization (DRO) problems with a wide range of applications in engineering and economics. In this paper, we propose a modified exchange algorithm for convex SDSIP that arises from ...
F. Luo and S. Mehrotra, "Decomposition algorithm for distributionally robust optimization using Wasserstein metric," 2017. Available at https: //arxiv.org/abs/1704.03920.F. Luo and S. Mehrotra, "Decomposition algorithm for distributionally robust optimization using Wasserstein metric," 2017. Available...
Mohajerin Esfahani, P., Kuhn, D.: Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations. Math. Program. 171, 115–166 (2018) Article MathSciNet Google Scholar Monteiro, R.D., Svaiter, B.F.: Complexity of variants of...
In this paper we propose a novel Q-learning algorithm allowing to solve distributionally robust Markov decision problems for which the ambiguity set of probability measures can be chosen arbitrarily as long as it comprises only a finite amount of measures. Therefore, our approach goes beyond the we...
Similarly, (Wang, et al. 2019) built a distributionally robust optimization model to minimize operating room opening costs and expected overtime. Show abstract Operating room planning and scheduling for outpatients and inpatients: A review and future research 2021, Operations Research for Health Care ...
Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang code 3 Designing the Topology of Graph Neural Networks: A Novel Feature Fusion Perspective Lanning Wei, Huan Zhao, Zhiqiang He code 3 Listing Ma...
Distributionally Robust Chance-Constrained Optimal Power Flow With Uncertain Renewables and Uncertain Reserves Provided by Loads Aggregations of electric loads can provide reserves to power systems, but their available reserve capacities are timevarying and not perfectly known when t... Y Zhang,S Shen,...
Robust optimization in the case of free distribution ignores distribution informations in the support set (Guo et al., 2023). In this paper, we address this problem by the distributionally robust optimization (DRO) method, which is suitable for the situation where only partial probability ...
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