Results 31 to 40 of about 2,032 (302)
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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Wasserstein Distributionally Robust Look-Ahead Economic Dispatch [PDF]
, 2021 We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy generation subject to uncertain operational constraints.
Hota, Ashish R. +6 more
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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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An Optimal Distributionally Robust Auction
CoRR, 2020 Updated literature review and exposition; results ...
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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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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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A Wasserstein-based distributionally robust neural network for non-intrusive load monitoring
Frontiers in Energy Research, 2023 Non-intrusive load monitoring (NILM) is a technique that uses electrical data analysis to disaggregate the total energy consumption of a building or home into the energy consumption of individual appliances. To address the data uncertainty problem in non-
Qing Zhang +6 more
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Data-driven distributionally robust optimization over a network via distributed semi-infinite programming [PDF]
, 2023 This paper focuses on solving a data-driven distributionally robust optimization problem over a network of agents. The agents aim to minimize the worst-case expected cost computed over a Wasserstein ambiguity set that is centered at the empirical ...
Hota, Ashish R. +4 more
core +1 more source