A piecewise linear upper bound on the network recourse function

DOI10.1007/BF02604638zbMath0632.90049OpenAlexW1981893768MaRDI QIDQ3770284

Stein W. Wallace

Publication date: 1987

Published in: Mathematical Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02604638

zbMATH Keywords

upper boundMadansky boundnetwork recourse functionpure minimum cost network flow problem

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Stochastic programming (90C15) Deterministic network models in operations research (90B10)

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Uses Software

• NETGEN

Cites Work

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• Refining bounds for stochastic linear programs with linearly transformed independent random variables
• Partitioning procedures for solving mixed-variables programming problems
• Bounds on the Expectation of a Convex Function of a Multivariate Random Variable
• Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs
• A tight upper bound for the expectation of a convex function of a multivariate random variable
• Designing approximation schemes for stochastic optimization problems, in particular for stochastic programs with recourse
• Solving stochastic programs with network recourse
• NETGEN: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Network Problems
• Solving stochastic programming problems with recourse including error bounds
• L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming