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Modeling & Solving Stochastic Programming Problems in Supply Chain Management Using Xpress-SP

  • Alan Dormer
  • Alkis Vazacopoulos
  • Nitin Verma
  • Horia Tipi
Part of the Applied Optimization book series (APOP, volume 98)

Abstract

Supply chains continually face the challenge of efficient decision-making in a complex environment coupled with uncertainty. While plenty of forecasting and analytical tools are available in the market to evaluate and enhance Supply Chain performance, the current functionalities are not sufficient to address issues related to efficient decision making under uncertainty. In this paper we discuss expanding the modeling paradigm to incorporate uncertain events naturally and concisely in a stochastic programming framework, and demonstrate how Xpress-SP—a, stochastic programming suite—can be used for modeling, solving and analyzing problems occurring in supply chain management.

Keywords

Supply Chain Supply Chain Management Stochastic Program Scenario Tree Global Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Alan Dormer
    • 1
  • Alkis Vazacopoulos
    • 1
  • Nitin Verma
    • 1
  • Horia Tipi
    • 1
  1. 1.Dash Optimization, IncEnglewood CliffsUSA

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