Results 31 to 40 of about 6,626 (272)
Energy Reports, 2023 To avoid the problem of insufficient flexibility of the power grid along the cz railway due to source-load fluctuations, a distributionally robust optimization method considering flexibility is proposed in this paper.
Jiawei Liu +5 more
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Relief Network Design Problem: A Distributionally Robust Optimization Approach [PDF]
چشمانداز مدیریت صنعتی, 2021 In this study, a robust two-stage risk-aversion optimization model is proposed for the multi-product relief network design problem. The comprehensive set of decisions for locating and reinforcing relief facilities, inventory planning, and distributing ...
Aliakbar Hasani
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An Optimal Distributionally Robust Auction
CoRR, 2020 Updated literature review and exposition; results ...
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Optimistic Distributionally Robust Policy Optimization
CoRR, 2020 Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), as the widely employed policy based reinforcement learning (RL) methods, are prone to converge to a sub-optimal solution as they limit the policy representation to a particular parametric distribution class.
Jun Song, Chaoyue Zhao
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Distributionally robust possibilistic optimization problems
Fuzzy Sets and Systems, 2023 In this paper a class of optimization problems with uncertain linear constraints is discussed. It is assumed that the constraint coefficients are random vectors whose probability distributions are only partially known. Possibility theory is used to model the imprecise probabilities.
Romain Guillaume +2 more
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, 2017 We consider stochastic programs where the distribution of the uncertain parameters is only observable through a finite training dataset. Using the Wasserstein metric, we construct a ball in the space of (multivariate and non-discrete) probability ...
Esfahani, Peyman Mohajerin, Kuhn, Daniel
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Distributionally robust optimization
Acta NumericaDistributionally robust optimization (DRO) studies decision problems under uncertainty where the probability distribution governing the uncertain problem parameters is itself uncertain. A key component of any DRO model is its ambiguity set, that is, a family of probability distributions consistent with any available structural or statistical ...
Daniel Kuhn 0001 +2 more
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Diance yu yibiaoIn order to adapt to the uncertainty of new energy, increase new energy consumption and reduce carbon emissions, an optimal scheduling model of integrated energy distribution network system is proposed based on vine Copula considering three uncertainties
YANG Mingjie +5 more
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Stochastic Optimal Power Flow Based on Data-Driven Distributionally Robust Optimization
, 2018 We propose a data-driven method to solve a stochastic optimal power flow (OPF) problem based on limited information about forecast error distributions. The objective is to determine power schedules for controllable devices in a power network to balance ...
camacho +8 more
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Nonlinear distributionally robust optimization
Mathematical ProgrammingThis article focuses on a class of distributionally robust optimization (DRO) problems where, unlike the growing body of the literature, the objective function is potentially nonlinear in the distribution. Existing methods to optimize nonlinear functions in probability space use the Frechet derivatives, which present theoretical and computational ...
Mohammed Rayyan Sheriff +1 more
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