Building and Solving Large-Scale Stochastic Programs on an Affordable Distributed Computing System

Emmanuel Fragnière, Jacek Gondzio, Jean Philippe Vial

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

We present an integrated procedure to build and solve big stochastic programming models. The individual components of the system - the modeling language, the solver and the hardware - are easily accessible, or a least affordable to a large audience. The procedure is applied to a simple financial model, which can be expanded to arbitrarily large sizes by enlarging the number of scenarios. We generated a model with one million scenarios, whose deterministic equivalent linear program has 1,111,112 constraints and 2,555,556 variables. We have been able to solve it on the cluster of ten PCs in less than 3 hours.

Original languageEnglish
Pages (from-to)167-187
Number of pages21
JournalAnnals of Operations Research
Volume99
Issue number1-4
DOIs
Publication statusPublished - 1 Dec 2000

Keywords

  • Algebraic modeling language
  • Decomposition methods
  • Distributed systems
  • Large-scale optimization
  • Stochastic programming

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

Cite this

Building and Solving Large-Scale Stochastic Programs on an Affordable Distributed Computing System. / Fragnière, Emmanuel; Gondzio, Jacek; Vial, Jean Philippe.

In: Annals of Operations Research, Vol. 99, No. 1-4, 01.12.2000, p. 167-187.

Research output: Contribution to journalArticle

@article{7ebfcc12723a4ef39a9ee8e2f152d14b,
title = "Building and Solving Large-Scale Stochastic Programs on an Affordable Distributed Computing System",
abstract = "We present an integrated procedure to build and solve big stochastic programming models. The individual components of the system - the modeling language, the solver and the hardware - are easily accessible, or a least affordable to a large audience. The procedure is applied to a simple financial model, which can be expanded to arbitrarily large sizes by enlarging the number of scenarios. We generated a model with one million scenarios, whose deterministic equivalent linear program has 1,111,112 constraints and 2,555,556 variables. We have been able to solve it on the cluster of ten PCs in less than 3 hours.",
keywords = "Algebraic modeling language, Decomposition methods, Distributed systems, Large-scale optimization, Stochastic programming",
author = "Emmanuel Fragni{\`e}re and Jacek Gondzio and Vial, {Jean Philippe}",
year = "2000",
month = "12",
day = "1",
doi = "10.1023/A:1019245101545",
language = "English",
volume = "99",
pages = "167--187",
journal = "Annals of Operations Research",
issn = "0254-5330",
publisher = "Springer Netherlands",
number = "1-4",

}

TY - JOUR

T1 - Building and Solving Large-Scale Stochastic Programs on an Affordable Distributed Computing System

AU - Fragnière, Emmanuel

AU - Gondzio, Jacek

AU - Vial, Jean Philippe

PY - 2000/12/1

Y1 - 2000/12/1

N2 - We present an integrated procedure to build and solve big stochastic programming models. The individual components of the system - the modeling language, the solver and the hardware - are easily accessible, or a least affordable to a large audience. The procedure is applied to a simple financial model, which can be expanded to arbitrarily large sizes by enlarging the number of scenarios. We generated a model with one million scenarios, whose deterministic equivalent linear program has 1,111,112 constraints and 2,555,556 variables. We have been able to solve it on the cluster of ten PCs in less than 3 hours.

AB - We present an integrated procedure to build and solve big stochastic programming models. The individual components of the system - the modeling language, the solver and the hardware - are easily accessible, or a least affordable to a large audience. The procedure is applied to a simple financial model, which can be expanded to arbitrarily large sizes by enlarging the number of scenarios. We generated a model with one million scenarios, whose deterministic equivalent linear program has 1,111,112 constraints and 2,555,556 variables. We have been able to solve it on the cluster of ten PCs in less than 3 hours.

KW - Algebraic modeling language

KW - Decomposition methods

KW - Distributed systems

KW - Large-scale optimization

KW - Stochastic programming

UR - http://www.scopus.com/inward/record.url?scp=0034560693&partnerID=8YFLogxK

U2 - 10.1023/A:1019245101545

DO - 10.1023/A:1019245101545

M3 - Article

VL - 99

SP - 167

EP - 187

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 1-4

ER -