Decomposition methods for multi-horizon stochastic programming

DOI10.1007/S10287-024-00509-YMaRDI QIDQ6538817

Asgeir Tomasgard, Hongyu Zhang, I. E. Grossmann

Publication date: 14 May 2024

Published in: Computational Management Science (Search for Journal in Brave)

zbMATH Keywords

stochastic programmingparallel computingbenders decompositionLagrangean decompositionmulti-horizon stochastic programmingprimal reduction

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

• Multi-horizon stochastic programming
• Bounds in multi-horizon stochastic programs
• Partitioning procedures for solving mixed-variables programming problems
• On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management
• Benders decomposition with adaptive oracles for large scale optimization
• Introduction to Stochastic Programming
• Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs
• Multistage stochastic programs with block-separable recourse
• JuMP: A Modeling Language for Mathematical Optimization

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