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Hybrid Branching

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5547))

Abstract

State-of-the-art solvers for Constraint Satisfaction Problems (CSP), Mixed Integer Programs (MIP), and satisfiability problems (SAT) are usually based on a branch-and-bound algorithm. The question how to split a problem into subproblems (branching) is in the core of any branch-and-bound algorithm. Branching on individual variables is very common in CSP, MIP, and SAT. The rules, however, which variable to choose for branching, differ significantly. In this paper, we present hybrid branching, which combines selection rules from all three fields.

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Author information

Authors and Affiliations

  1. ILOG, an IBM company, Ober-Eschbacher Str. 109, 61352, Bad Homburg, Germany

    Tobias Achterberg

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

    Timo Berthold

Authors
  1. Tobias Achterberg
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  2. Timo Berthold
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Editor information

Editors and Affiliations

  1. Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, PA 15213, Pittsburgh, USA

    Willem-Jan van Hoeve

  2. Carnegie Mellon University, USA

    John N. Hooker

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© 2009 Springer-Verlag Berlin Heidelberg

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Achterberg, T., Berthold, T. (2009). Hybrid Branching. In: van Hoeve, WJ., Hooker, J.N. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2009. Lecture Notes in Computer Science, vol 5547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01929-6_23

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  • DOI: https://doi.org/10.1007/978-3-642-01929-6_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01928-9

  • Online ISBN: 978-3-642-01929-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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