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Experiments with Conflict Analysis in Mixed Integer Programming

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Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10335))

Abstract

The analysis of infeasible subproblems plays an important role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications, obtained by domain propagation, that led to infeasibility. The result of the analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept has its origin in solving satisfiability problems and is similarly used in constraint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. The dual LP solution provides a set of multipliers that can be used to generate a single new globally valid linear constraint. The main contribution of this short paper is an empirical evaluation of two ways to combine both approaches. Experiments are carried out on general MIP instances from standard public test sets such as Miplib2010; the presented algorithms have been implemented within the non-commercial MIP solver SCIP. Moreover, we present a pool-based approach to manage conflicts which addresses the way a MIP solver traverses the search tree better than aging strategies known from SAT solving.

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Notes

  1. 1.

    The instances are part of the contributed section of Miplib2003.

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Acknowledgments

The work for this article has been conducted within the Research Campus Modal funded by the German Federal Ministry of Education and Research (fund number 05M14ZAM). We thank the anonymous reviewers for their valuable suggestions and helpful comments.

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Authors and Affiliations

  1. Zuse Institute Berlin, Takustr. 7, 14195, Berlin, Germany

    Jakob Witzig

  2. Fair Isaac Germany GmbH, Takustr. 7, 14195, Berlin, Germany

    Timo Berthold & Stefan Heinz

Authors
  1. Jakob Witzig
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  2. Timo Berthold
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  3. Stefan Heinz
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Correspondence to Jakob Witzig .

Editor information

Editors and Affiliations

  1. University of Padua, Padua, Italy

    Domenico Salvagnin

  2. University of Bologna, Bologna, Italy

    Michele Lombardi

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Witzig, J., Berthold, T., Heinz, S. (2017). Experiments with Conflict Analysis in Mixed Integer Programming. In: Salvagnin, D., Lombardi, M. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2017. Lecture Notes in Computer Science(), vol 10335. Springer, Cham. https://doi.org/10.1007/978-3-319-59776-8_17

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  • DOI: https://doi.org/10.1007/978-3-319-59776-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59775-1

  • Online ISBN: 978-3-319-59776-8

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