Skip to main content
Log in

Automatic Formulation of Stochastic Programs Via an Algebraic Modeling Language

  • Original Paper
  • Published:
Computational Management Science Aims and scope Submit manuscript

Abstract

This paper presents an open source tool that automatically generates the so-called deterministic equivalent in stochastic programming. The tool is based on the algebraic modeling language ampl. The user is only required to provide the deterministic version of the stochastic problem and the information on the stochastic process, either as scenarios or as a transitions-based event tree.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Birge JR, Louveaux F (1997) Introduction to stochastic programming. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Condevaux-Lanloy C (2004) Extensions de l’interface entre langages de modé elisation et codes d’optimisation: application à la programmation stochastique multi-étapes linéaire et non-linéaire. PhD Thesis, University of Geneva

  • Condevaux-Lanloy C, Fragnière E, King A (2002) SISP, simplified interface for stochastic programming. Optim Methods Softw 17(3):423–443

    Article  Google Scholar 

  • Dormer A, Vazacopoulos A, Verma N, Tipi H (2005) Modeling & solving stochastic programming problems in supply chain management using XPRESS-SP. Supply Chain Optimization; Geunes and Pardalos Eds, (2005) 1–27

  • Edwards J, Birge J, King A, Nazareth L (1985) A standard input format for computer codes which solve stochastic programs with recourse and a library of utilities to simplify its use. In: Working Paper WP-85-03, International Institute for Applied Systems Analysis, Laxenburg, Austria

  • Fourer R, Gay D, Kernigham B (1993) ampl: a modeling language for mathematical programming. The Scientific Press Series, San Francisco

    Google Scholar 

  • Fourer R, Gay D (1997) Proposals for stochastic programming in the ampl modeling language. In: Session WE4-G-IN11, International symposium on mathematical programming, lausanne, August 27

  • Fourer R, Lopes L (2004) A filtration-oriented system for modeling in stochastic programming. In: Technical report, Department of systems and industrial engineering, University of Arizona

  • Fragnière E, Gondzio J, Sarkissian R, Vial J.-Ph (2000a) Structure exploiting tool in algebraic modeling languages. Manage Sci 46:1145–1158

    Article  Google Scholar 

  • Fragnière E, Gondzio J, Vial J.-Ph (2000) Building and solving large-scale stochastic programs on an affordable distributed computing system. Ann Oper Res 99(1/4):167–187

    Article  Google Scholar 

  • Friedl JEF (1997) Mastering regular expressions. O’Reilly & Associates, Cambridge

    Google Scholar 

  • Gassmann HI, Ireland AM (1996) On the formulation of stochastic linear programs using algebraic modeling languages. Ann Oper Res 64:83–112

    Article  Google Scholar 

  • Gassmann HI, Schweitzer E (2001) A comprehensive input format for stochastic linear programs. Ann Oper Res 104:89–125

    Article  Google Scholar 

  • Høyland K, Wallace S (2001) Generating scenario trees for multi-stage decision problems. Manage Sci 47:295–307

    Article  Google Scholar 

  • IBM (1998) OSL Stochastic Extensions: Guide and Reference, ©IBM Corp.,

  • Kall P, Wallace S (1994) Stochastic programming. Wiley, New York

    Google Scholar 

  • Makhorin A (2005) GNU linear programming kit: reference manual. Free software foundation, 4.8

  • Murtagh B (1981) Advanced linear programming: computation and practice. McGraw-Hill, New York

    Google Scholar 

  • Pflug G (1989) Optimal scenario tree generation for multiperiod financial planning. Math Program 89:251–271

    Article  Google Scholar 

  • Valente P, Mitra G, Poojari C, Kyriakis T (2001) Software tools for stochastic programming: a stochastic programming integrated environment (SPInE). In: Technical report, Brunel University

  • van Delft Ch, Vial J.-Ph (2004) A practical implementation of stochastic programming: an application to the evaluation of option contracts in supply chain. Automatica 40:743–756

    Article  Google Scholar 

  • Wall L, Christiansen T, Orwant J (2001) Programming Perl, 3rd ed. O’Reilly & Associates, Cambridge

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. Thénié.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Thénié, J., van Delft, C. & Vial, J.P. Automatic Formulation of Stochastic Programs Via an Algebraic Modeling Language. CMS 4, 17–40 (2007). https://doi.org/10.1007/s10287-006-0022-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10287-006-0022-z

Keywords

MSC code

Navigation