Compromise policy for multi-stage stochastic linear programming: variance and bias reduction

DOI10.1016/j.cor.2022.106132MaRDI QIDQ6164357

Jiajun Xu, Suvrajeet Sen

Publication date: 4 July 2023

Published in: Computers \& Operations Research (Search for Journal in Brave)

zbMATH Keywords

bias reductionvariance reductiondistributed computingonline optimizationmulti-stage stochastic programmingensemble model

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Related Items (1)

On the safe side of stochastic programming: bounds and approximations

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A comment on ``Computational complexity of stochastic programming problems
• Analysis of stochastic dual dynamic programming method
• On the convergence of stochastic dual dynamic programming and related methods
• Multi-stage stochastic optimization applied to energy planning
• Finite master programs in regularized stochastic decomposition
• Multistage stochastic programming model for electric power capacity expansion problem
• Assessing policy quality in a multistage stochastic program for long-term hydrothermal scheduling
• Computational complexity of stochastic programming problems
• Assessing solution quality in stochastic programs
• On complexity of multistage stochastic programs
• Concepts, Technical Issues, and Uses of the Russell-Yasuda Kasai Financial Planning Model
• Mitigating Uncertainty via Compromise Decisions in Two-Stage Stochastic Linear Programming: Variance Reduction
• Bias and Variance Approximation in Value Function Estimates
• SDDP.jl: A Julia Package for Stochastic Dual Dynamic Programming
• Stochastic Dynamic Linear Programming: A Sequential Sampling Algorithm for Multistage Stochastic Linear Programming
• Approximate Dynamic Programming

This page was built for publication: Compromise policy for multi-stage stochastic linear programming: variance and bias reduction