This webpage is a collection of links to information on Stochastic Programming. Stochastic programming concerns with mathematical programming problems where some of the problems parameters are uncertain. For a quick introduction to this exciting field of optimization, try the links in the Introduction section.
 

Send your comments and suggestions to Shabbir Ahmed (sahmed@isye.gatech.edu).
 
 

• The official (COSP) stochastic programming site: stoprog.org
• Stochastic Programming at the University of Michigan
• Stochastic Programming at Argonne National Labs
• Claus Caroe's Stochastic Programming Site
• Stochastic Programming in Beasly's OR-Notes
• Stochastic Programming: Computational Issues and Challenges by Suvrajeet Sen

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ANNOUNCEMENTS:

• Subscribe to the NEW COSP mailing list for the latest on Stochastic Programming
• IX International Conference on Stochastic Programming, Berlin, Germany. Aug.25- Sep.1, 2001.
• IFIP/IIASA/GAMM-Workshop on DYNAMIC STOCHASTIC OPTIMIZATION, IIASA Laxenburg, March 11-14, 2002.
• Check out Optimization Online for optimization eprints.
• Check out Stochastic Programming E-Print Series (SPEPS) for Stochastic Programming preprints.

RESEARCH GROUPS & PEOPLE:

GROUPS:

• IBM Research in Stochastic Programming
• Stochastic Programming at the University of Auckland

PEOPLE:

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PAPERS:

• Optimization Online
• Stochastic Programming E-Print Series (SPEPS)
• Van der Vlerk's searchable Stochastic Programming Bibliography
• Online preprints from John Birge
• Online preprints from Alexander Shapiro
• Online preprints from Roger Wets
• Working papers from IIASA
• Links to preprints at Chalmers University
• Stochastic Programming Books from Amazon.com

SOFTWARE:

• SLPIOR
• Description: An interactive model management system for two stage stochastic programs. Handles algebraic structure and scenario generation. Menu driven problem input or through SMPS files.
• Implemented algorithms: Benders, Regularized and Stochastic Decomposition, Interior point methods etc.
• Platform: DOS, Windows.
• Requirement: GAMS.
• Contact: Prof. Peter Kall, Instt. for Operations Research, University of Zurich, Switzerland.

• SQG
• Description: Implementation of Ermoliev's Stochastic Quasi-Gradient Method.
• Platform: Unix, DOS, Windows.
• Contact: Prof. Alexei A. Gaivoronski . Also see the software page.

• MSLiP
• Description: FORTRAN code for multistage stochastic programming. Supports an arbitrary number of time periods and various types of random structures for the input data. Problem input in SMPS format.
• Implemented algorithms: Nested benders decomposition.
• Platform: Portable on Unix, DOS, Macintosh,VMAX.Requirement: stand alone.
• More information: MSLiP 8.3 User Guide.
• Contact: Dr. H.I. Gassmann, Associate Professor, School of Business Administration, Dalhousie University Halifax, Nova Scotia,Canada. Email: Horand.Gassmann@dal.ca

• IBM Stochastic Solutions
• Description: First commercial grade software for multi-stage stochastic linear programming.
• Free academic licenses!
• More information: IBM Stochastic Solutions

• NEOS Solver
• Description: Web based stochastic programming solvers. Accepts electronic problem submission in SMPS format.
• Implemented algorithms: Mehrotra's Augmented system LP solver and MSLiP.
• Platform: Web based.
• More information: The NEOS server

• NEOS VERIFY
• Description: Provides confidence intervals for a candidate solution to a stochastic program.
• Platform: Web based.
• More information: NEOS Verfiy

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TEST PROBLEMS:

• Test problems compiled by Steve Wright
• Andrew Felt's Test Set
• The POSTS problem set
• Watson Pension fund management problem set
• Interactive Stochastic Programming case study in the NEOS guide