A multistage distributionally robust optimization approach to water allocation under climate uncertainty
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Publication:6106506
DOI10.1016/j.ejor.2022.06.049arXiv2005.07811OpenAlexW3027230906WikidataQ114194225 ScholiaQ114194225MaRDI QIDQ6106506
Publication date: 3 July 2023
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2005.07811
water resourcesphi-divergencesmultistage distributionally robust optimizationor in environment and climate changenested benders decomposition
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Cites Work
- Unnamed Item
- Data-driven chance constrained stochastic program
- Evaluating policies in risk-averse multi-stage stochastic programming
- Analysis of stochastic dual dynamic programming method
- Convexity and concavity properties of the optimal value function in parametric nonlinear programming
- Maxmin expected utility with non-unique prior
- Multi-stage stochastic optimization applied to energy planning
- Modeling time-dependent randomness in stochastic dual dynamic programming
- A stochastic dynamic programming approach to analyze adaptation to climate change -- application to groundwater irrigation in India
- The impact of global climate change on water quantity and quality: a system dynamics approach to the US-Mexican transborder region
- Risk-averse two-stage stochastic programming with an application to disaster management
- Distributionally robust SDDP
- A time-consistent Benders decomposition method for multistage distributionally robust stochastic optimization with a scenario tree structure
- Tutorial on risk neutral, distributionally robust and risk averse multistage stochastic programming
- Time (in)consistency of multistage distributionally robust inventory models with moment constraints
- Frameworks and results in distributionally robust optimization
- Entropy based risk measures
- Controlling risk and demand ambiguity in newsvendor models
- On distributionally robust multiperiod stochastic optimization
- MEASURING DISTRIBUTION MODEL RISK
- Decomposition Algorithms for Risk-Averse Multistage Stochastic Programs with Application to Water Allocation under Uncertainty
- Convergence Analysis of Sampling-Based Decomposition Methods for Risk-Averse Multistage Stochastic Convex Programs
- Multistage Stochastic Optimization
- Maximum-loss, minimum-win and the Esscher pricing principle
- Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs
- Distributionally Robust Stochastic Dual Dynamic Programming
- Mathematical Foundations of Distributionally Robust Multistage Optimization
- Calibration of Distributionally Robust Empirical Optimization Models
- Exact Converging Bounds for Stochastic Dual Dynamic Programming via Fenchel Duality
- Robust Dual Dynamic Programming
- On Solving Multistage Stochastic Programs with Coherent Risk Measures
- On the Convergence of Decomposition Methods for Multistage Stochastic Convex Programs
- Expected Value Minimization in Information Theoretic Multiple Priors Models
- Rectangular Sets of Probability Measures
- Distributionally Robust Inventory Control When Demand Is a Martingale
- Convex analysis and monotone operator theory in Hilbert spaces
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