Advertisement

Stochastic Programming Extensions

  • William E. Hart
  • Carl D. Laird
  • Jean-Paul Watson
  • David L. Woodruff
  • Gabriel A. Hackebeil
  • Bethany L. Nicholson
  • John D. Siirola
Chapter
  • 5.2k Downloads
Part of the Springer Optimization and Its Applications book series (SOIA, volume 67)

Abstract

This chapter describes PySP, a stochastic programming extension to Pyomo. PySP enables the expression of stochastic programming problems as extensions of deterministic models, which are often formulated first. To formulate a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree with associated uncertain parameters in Pyomo. Given these two models, PySP provides two paths for solving the corresponding stochastic program. The first alternative involves PySP writing the extensive form and invoking a standard deterministic solver. For more complex stochastic programs, PySP includes an implementation of Rockafellar and Wets’ Progressive Hedging algorithm, which provides an effective heuristic for approximating general multi-stage, mixed-integer stochastic programs. By leveraging the combination of a high-level programming language and the embedding of the base deterministic model in that language, PySP provides completely generic and highly configurable solver implementations.

Keywords

Stochastic Program Extensive Form Scenario Tree Time Stage Stochastic Linear Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • William E. Hart
    • 1
  • Carl D. Laird
    • 1
  • Jean-Paul Watson
    • 1
  • David L. Woodruff
    • 2
  • Gabriel A. Hackebeil
    • 3
  • Bethany L. Nicholson
    • 1
  • John D. Siirola
    • 1
  1. 1.Sandia National LaboratoriesAlbuquerqueUSA
  2. 2.Graduate School of ManagementUniversity of California, DavisDavisUSA
  3. 3.Department of Industrial and Operations EngineeringUniversity of MichiganAnn ArborUSA

Personalised recommendations