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Branching Constraint Satisfaction Problems and Markov Decision Problems Compared

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  • David Fowler
  • Kenneth Brown

Abstract

Branching Constraint Satisfaction Problems (BCSPs) model a class of uncertain dynamic resource allocation problems. We describe the features of BCSPs, and show that the associated decision problem is NP-complete. Markov Decision Problems could be used in place of BCSPs, but we show analytically and empirically that, for the class of problems in question, the BCSP algorithms are more efficient than the related MDP algorithms. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • David Fowler & Kenneth Brown, 2003. "Branching Constraint Satisfaction Problems and Markov Decision Problems Compared," Annals of Operations Research, Springer, vol. 118(1), pages 85-100, February.
    • Handle: RePEc:spr:annopr:v:118:y:2003:i:1:p:85-100:10.1023/a:1021853506616
    DOI: 10.1023/A:1021853506616
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    Cited by:

    1. Hamed Fahimi & Claude-Guy Quimper, 2023. "Overload-Checking and Edge-Finding for Robust Cumulative Scheduling," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1419-1438, November.

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