A practical implementation of stochastic programming: an application to the evaluation of option contracts in supply chains

Christian van Delft () and Jean-Philippe Vial
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Christian van Delft: GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique

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Abstract: Stochastic programming is a powerful analytical method in order to solve sequential decision-making problems under uncertainty. We describe an approach to build such stochastic linear programming models. We show that algebraic modeling languages make it possible for non-specialist users to formulate complex problems and have solved them by powerful commercial solvers. We illustrate our point in the case of option contracts in supply chain management and propose a numerical analysis of performance. We propose easy-to-implement discretization procedures of the stochastic process in order to limit the size of the event tree in a multi-period environment.

Keywords: Linear stochastic programming; Algebraic modeling language; Sequential decision-making problem; Event tree (search for similar items in EconPapers)
Date: 2004-05-01
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Citations: View citations in EconPapers (7)

Published in Automatica, 2004, Vol.40,n°5, pp.743-756. ⟨10.1016/j.automatica.2003.12.008⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00471409

DOI: 10.1016/j.automatica.2003.12.008

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