Software & Test Sets

This page was originally compiled by Shabbir Ahmed.

Software

The following is a brief description of some of the available stochastic programming software. The list is in no way complete or accurate. Please inform the webmaster of any deletions or discrepancies.

[NEW] The booklet On Selected Software for Stochastic Programming (edited by Milos Kopa) deals with several software products for solving (multistage) stochastic programs. Each product is briefly described and applied to solving an investment problem formulated as three-stage linear stochastic program. The goal of the book is to introduce the basic ideas of these products and to give an example how these products can be used for solving real-life problems.
Further details and download instructions.

Stochastic Modeling Interface (SMI)

  • Description: SMI from COIN-OR provides various utilities for multi-stage stochastic programming model management.
  • Implemented utilities: The current release implements a multiperiod scenario stochastic programming object, supports an SMPS file reader method, a direct scenario generation method, a method to generate a deterministic equivalent, and several methods to get solution data by scenario.
  • Platform: Linux using g++ V3.1.1 and Windows using Microsoft Visual C++ V6.
  • Availability: SMI is open source under the Common Public License. Anyone can use the code for any purpose. Contributions are definitely encouraged!
  • Contact: Alan J. King.

SLP-IOR

  • Description: SLP-IOR is an interactive model management system for stochastic linear programs. It includes support for two- and multistage programs with recourse, problems with individual and joint chance constraints, and problems with integrated chance constraints and CVaR constraints or objective. It handles the algebraic structure and scenario generation. Problems can be input via menus, through SMPS files, and via GAMS interface.
  • Implemented algorithms: Benders, Regularized and Stochastic Decomposition, Discrete Approximation, Interior point methods, Supporting hyperplane, Central cutting plane, etc.
  • Platform: Windows
  • Contact: Prof. Peter Kall or Dr. Janos Mayer, Inst. for Operations Research, University of Zurich, Switzerland.

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
  • Availability: The code is available to universities and academic institutions for reseach and teaching purposes. A version of the code is also running at the NEOS solver, see below.
  • Contact: Dr. H.I. Gassmann, Professor, School of Business Administration, Dalhousie University Halifax, Nova Scotia Canada. Email: Horand.Gassmann@dal.ca

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

SPInE

  • Description: An integrated modelling and solver system based on extended language constructs designed to facilitate the formulation of scenario based recourse problems (two-stage and multistage). Produces model instances in SMPS format and integrates a stochastic solver based on Benders decomposition. Available also as an add-in to the MPL modelling system.
  • Implemented algorithms: Benders decomposition, deterministic equivalent solved via Interior Point Method or Sparse Simplex.
  • Platform: Windows.
  • Requirement: (MPL or OptiMax component library).
  • More information: Technical Report on SPInE.
  • Contact: Prof. Gautam Mitra, Mr Patrick Valente, or Dr Chandra A. Poojari, Centre for the Analysis of Risk and Optimisation Modelling Application (CARISMA), Brunel University, United Kingdom.

BNBS

  • Description: An implementation of the nested Benders algorithm, written in C. Problem input is in the SMPS-format, although the program only supports the INDEP, BLOCKS, and SCENARIOS tags in the stoch-file. The program supports an arbitrary number of time periods and time periods may be aggregated arbitrarily. The number of subproblems which contribute to one cut in the algorithm may be set arbitrarily, in effect implementing single-cut, multi-cut and anything in between.
  • Implemented algorithms: Nested Benders decomposition
  • Platform: Tested on Sun Solaris, Linux and windows (via mingw), but should be portable across any UNIX. Features such as timing and memory information is not available on all platforms
  • Requirements: Flex and bison are required for compilation. An lp solver is needed, interfaces for CPLEX 6.5 GLPK 4.0 and SOPLEX 1.2.1 are implemented, although the SOPLEX interface does not work for all problems.
  • Availability: The code may be used for research and teaching at academic institutions, by staff or student. Note that an LP-solver must be obtained separately, and that the supported solvers may have other conditions for their use.
  • Contact: Fredrik Altenstedt

AIMMS

  • Description: AIMMS offers support for generating a stochastic LP/MIP recourse model from any given deterministic model, without the need to reformulate the deterministic model. By only supplying additional attributes for selected parameters, variables and constraints, AIMMS can generate both a deterministic and recourse model from the same formulation. Various user adaptable templates for generating a scenario tree and the corresponding stochastic input data for the recourse model are available in the form of a system module which can be imported into any AIMMS application.
  • Implemented algorithms: To solve the recourse model, AIMMS can generate and solve the corresponding deterministic equivalent. In addition, AIMMS includes an algorithm to solve stochastic models using a stochastic Benders approach and a module to visualize stochastic scenario trees.
  • Platform: Windows and Linux.
  • Availability: Commercial; Download a free trial license of AIMMS
  • Contact: Paragon.

Data Formats

SMPS, a standard input format for multiperiod stochastic programs based on MPS, was introduced in 1987 by Birge et al.. See The SMPS format for stochastic linear programs for a current description, and the corresponding Fortran 90 implementation SMPS reader by Gus Gassmann.

Test Sets

Links updated on June 20th 2009.