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On the Consistent Path Problem

Author

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  • Leonardo Lozano

    (Operations, Business Analytics & Information Systems, University of Cincinnati, Cincinnati, Ohio 45221)

  • David Bergman

    (Operations and Information Management, University of Connecticut, Storrs, Connecticut 06260)

  • J. Cole Smith

    (Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, New York 13210)

Abstract

The application of decision diagrams in combinatorial optimization has proliferated in the last decade. In recent years, authors have begun to investigate how to use not one, but a set of diagrams, to model constraints and objective function terms. Optimizing over a collection of decision diagrams, the problem we refer to as the consistent path problem (CPP) can be addressed by associating a network-flow model with each decision diagram, jointly linked through channeling constraints. A direct application of integer programming to the ensuing model has already been shown to result in algorithms that provide orders-of-magnitude performance gains over classical methods. Lacking, however, is a careful study of dedicated solution methods designed to solve the CPP. This paper provides a detailed study of the CPP, including a discussion on complexity results and a complete polyhedral analysis. We propose a cut-generation algorithm, which, under a structured ordering property, finds a cut, if one exists, through an application of the classical maximum flow problem, albeit in an exponentially sized network. We use this procedure to fuel a cutting-plane algorithm that is applied to unconstrained binary cubic optimization and a variant of the market split problem, resulting in an algorithm that compares favorably with CPLEX, using standard integer programming formulations for both problems.

Suggested Citation

  • Leonardo Lozano & David Bergman & J. Cole Smith, 2020. "On the Consistent Path Problem," Operations Research, INFORMS, vol. 68(6), pages 1913-1931, November.
  • Handle: RePEc:inm:oropre:v:68:y:2020:i:6:p:1913-1931
    DOI: 10.1287/opre.2020.1979
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    References listed on IDEAS

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    1. Alfred Wassermann, 2002. "Attacking the Market Split Problem with Lattice Point Enumeration," Journal of Combinatorial Optimization, Springer, vol. 6(1), pages 5-16, March.
    2. Alberto Del Pia & Aida Khajavirad, 2017. "A Polyhedral Study of Binary Polynomial Programs," Mathematics of Operations Research, INFORMS, vol. 42(2), pages 389-410, May.
    3. Gary Kochenberger & Jin-Kao Hao & Fred Glover & Mark Lewis & Zhipeng Lü & Haibo Wang & Yang Wang, 2014. "The unconstrained binary quadratic programming problem: a survey," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 58-81, July.
    4. Yanjun Wang & Zhian Liang, 2010. "Global optimality conditions for cubic minimization problem with box or binary constraints," Journal of Global Optimization, Springer, vol. 47(4), pages 583-595, August.
    5. Gérard Cornuéjols & Milind Dawande, 1999. "A Class of Hard Small 0-1 Programs," INFORMS Journal on Computing, INFORMS, vol. 11(2), pages 205-210, May.
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    Cited by:

    1. Alexey A. Bochkarev & J. Cole Smith, 2023. "On Aligning Non-Order-Associated Binary Decision Diagrams," INFORMS Journal on Computing, INFORMS, vol. 35(5), pages 910-928, September.

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