Results 11 to 20 of about 6,467 (228)
IEEE Access, 2021 Since optimal portfolio strategy depends heavily on the distribution of uncertain returns, this article proposes a new method for the portfolio optimization problem with respect to distribution uncertainty.
Ningning Du, Yankui Liu, Ying Liu
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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation [PDF]
Dianli jianshe[Objective] Multi-energy microgrids（MEMGs）can integrate multiple energy carriers to improve energy efficiency，thereby contributing to the achievement of "dual carbon" goals. [Methods] This study proposes a data-driven distributionally robust optimization
LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi
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Frameworks and Results in Distributionally Robust Optimization
Open Journal of Mathematical Optimization, 2022 The concepts of risk aversion, chance-constrained optimization, and robust optimization have developed significantly over the last decade. The statistical learning community has also witnessed a rapid theoretical and applied growth by relying on these ...
Rahimian, Hamed, Mehrotra, Sanjay
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Robustness to dependency in portfolio optimization using overlapping marginals [PDF]
, 2015 In this paper, we develop a distributionally robust portfolio optimization model where the robustness is across different dependency structures among the random losses.
Doan, Xuan Vinh +2 more
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Energy Reports, 2023 This paper proposes a distributed data-driven distributionally robust volt/var control (DDDR-VVC) approach which schedules on-load-tap changer (OLTC), capacitor banks (CBs) and Photovoltaic (PV) inverters coordinately.
Peishuai Li +4 more
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Data-Driven Chance Constrained Optimization under Wasserstein Ambiguity Sets [PDF]
, 2018 We present a data-driven approach for distributionally robust chance constrained optimization problems (DRCCPs). We consider the case where the decision maker has access to a finite number of samples or realizations of the uncertainty.
Cherukuri, Ashish +2 more
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A distributionally robust perspective on uncertainty quantification and chance constrained programming [PDF]
, 2015 The objective of uncertainty quantification is to certify that a given physical, engineering or economic system satisfies multiple safety conditions with high probability.
Hanasusanto, GA +3 more
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The Distributionally Robust Optimization Reformulation for Stochastic Complementarity Problems
Abstract and Applied Analysis, 2014 We investigate the stochastic linear complementarity problem affinely affected by the uncertain parameters. Assuming that we have only limited information about the uncertain parameters, such as the first two moments or the first two moments as well as ...
Liyan Xu, Bo Yu, Wei Liu
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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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