Value Interchangeability in Scenario Generation

  • Steven D. Prestwich
  • Marco Laumanns
  • Ban Kawas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8124)


Several types of symmetry have been identified and exploited in Constraint Programming, leading to large reductions in search time. We present a novel application of one such form of symmetry: detecting dynamic value interchangeability in the random variables of a 2-stage stochastic problem. We use a real-world problem from the literature: finding an optimal investment plan to strengthen a transportation network, given that a future earthquake probabilistically destroys links in the network. Detecting interchangeabilities enables us to bundle together many equivalent scenarios, drastically reducing the size of the problem and allowing the exact solution of cases previously considered intractable and solved only approximately.


Mixed Integer Programming Stochastic Program Constraint Programming Constraint Satisfaction Problem Stochastic Dominance 
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-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Steven D. Prestwich
    • 1
  • Marco Laumanns
    • 2
  • Ban Kawas
    • 3
  1. 1.Cork Constraint Computation Centre, Department of Computer ScienceUniversity College CorkIreland
  2. 2.IBM Research – ZurichRueschlikonSwitzerland
  3. 3.IBM Thomas J. Watson Research CenterUSA

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