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

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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.

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Authors and Affiliations

  1. HEC, Université de Lausanne, BSFH1, CH-1015, Dorigny-Lausanne, Switzerland

    Emmanuel Fragnière

  2. Department of Mathematics and Statistics, The University of Edinburgh, James Clerk Maxwell Building, King's Buildings, EH9 3JZ, Edinburgh, UK

    Jacek Gondzio

  3. Logilab, HEC, Section of Management Studies, University of Geneva, 40 Boulevard du Pont d'Arve, CH-1211, Geneva 4, Switzerland ejean-philippe.vial@hec.unige.ch

    Jean-Philippe Vial

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  1. Emmanuel Fragnière
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  2. Jacek Gondzio
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  3. Jean-Philippe Vial
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Fragnière, E., Gondzio, J. & Vial, JP. Building and Solving Large-Scale Stochastic Programs on an Affordable Distributed Computing System. Annals of Operations Research 99, 167–187 (2000). https://doi.org/10.1023/A:1019245101545

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