A Multicut Algorithm for Two-Stage Stochastic Linear Programs.

Abstract

Outer linearization methods, such as Van Slyke and Wets's L-shaped method for stochastic linear programs, generally apply a single cut on the nonlinear objective at each major iteration. The structure of stochastic programs allows for several cuts to be placed at once. This paper describes a multicut algorithm to carry out this procedure. It presents experimental and theoretical justification for reductions in major iterations. Keywords: Operations research.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1986
Accession Number
ADA186148

Entities

People

  • Francois V. Louveaux
  • John R. Birge

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computational Science
  • Computations
  • Computer Programming
  • Convex Sets
  • Decomposition
  • Engineering
  • Iterations
  • Linear Programming
  • Mathematical Programming
  • Michigan
  • Operations Research
  • Probability
  • Random Variables
  • Sequences
  • Simplex Method

Fields of Study

  • Engineering

Readers

  • Operations Research