A data-driven approach for a class of stochastic dynamic optimization problems
From MaRDI portal
Publication:2057219
DOI10.1007/s10589-021-00320-4zbMath1481.90237OpenAlexW3203981230MaRDI QIDQ2057219
Thuener Silva, Davi Michel Valladão, Tito Homem-de-mello
Publication date: 8 December 2021
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10589-021-00320-4
stochastic programminghidden Markov modelsstochastic dual dynamic programmingrisk constraintsdistributionally robust dynamic optimization
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Risk aversion in multistage stochastic programming: a modeling and algorithmic perspective
- Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion
- Strategic asset allocation under a fractional hidden Markov model
- Analysis of stochastic dual dynamic programming method
- On general minimax theorems
- On the convergence of stochastic dual dynamic programming and related methods
- Multi-stage stochastic optimization applied to energy planning
- An application of hidden Markov models to asset allocation problems
- Modeling time-dependent randomness in stochastic dual dynamic programming
- Identifying effective scenarios in distributionally robust stochastic programs with total variation distance
- An adaptive robust portfolio optimization model with loss constraints based on data-driven polyhedral uncertainty sets
- Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations
- Distributionally robust SDDP
- Hidden Markov models in finance. Further developments and applications. Volume II
- Risk neutral and risk averse stochastic dual dynamic programming method
- Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
- Time consistency and risk averse dynamic decision models: definition, interpretation and practical consequences
- Partially observable multistage stochastic programming
- Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
- Distributionally Robust Optimization and Its Tractable Approximations
- On a Class of Minimax Stochastic Programs
- Minimax analysis of stochastic problems
- Distributionally Robust Stochastic Dual Dynamic Programming
- On Solving Multistage Stochastic Programs with Coherent Risk Measures
- Robust Wasserstein profile inference and applications to machine learning
- Ambiguity in portfolio selection
- COHERENT ACCEPTABILITY MEASURES IN MULTIPERIOD MODELS
- JuMP: A Modeling Language for Mathematical Optimization
This page was built for publication: A data-driven approach for a class of stochastic dynamic optimization problems