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Optimization Bounds from Binary Decision Diagrams

(Extended Abstract)
  • David Bergman
  • Andre A. Ciré
  • Willem-Jan van Hoeve
  • John N. Hooker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8656)

Abstract

Bounds on the optimal value are often indispensable for the practical solution of discrete optimization problems, particularly in the branching procedures used by constraint programming (CP) and integer programming solvers. Such bounds are frequently obtained by solving a continuous relaxation of the problem, perhaps a linear programming (LP) relaxation. In this paper, we explore an alternative strategy of obtaining bounds from a discrete relaxation, namely a binary decision diagram (BDD). Such a strategy is particularly suitable for CP, because BDDs provide enhanced propagation as well [2-5].

Keywords

Boolean Function Constraint Programming Linear Programming Relaxation Discrete Optimization Problem Binary Decision Diagram 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • David Bergman
    • 1
  • Andre A. Ciré
    • 2
  • Willem-Jan van Hoeve
    • 2
  • John N. Hooker
    • 2
  1. 1.University of ConnecticutUSA
  2. 2.Carnegie Mellon UniversityUSA

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