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International Conference on Principles and Practice of Constraint Programming

CP 2014: Principles and Practice of Constraint Programming pp 108–124Cite as

Sequential Time Splitting and Bounds Communication for a Portfolio of Optimization Solvers

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8656))

Abstract

Scheduling a subset of solvers belonging to a given portfolio has proven to be a good strategy when solving Constraint Satisfaction Problems (CSPs). In this paper, we show that this approach can also be effective for Constraint Optimization Problems (COPs). Unlike CSPs, sequential execution of optimization solvers can communicate information in the form of bounds to improve the performance of the following solvers. We provide a hybrid and flexible portfolio approach that combines static and dynamic time splitting for solving a given COP. Empirical evaluations show the approach is promising and sometimes even able to outperform the best solver of the porfolio.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and Engineering/Lab. Focus INRIA, University of Bologna, Italy

    Roberto Amadini

  2. National ICT Australia, Department of Computing and Information Systems, University of Melbourne, VIC, 3010, Australia

    Peter J. Stuckey

Authors
  1. Roberto Amadini
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  2. Peter J. Stuckey
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Editor information

Editors and Affiliations

  1. Insight Centre for Data Analytics, School of Computer Science and IT, University College Cork, Western Road, Cork, Ireland

    Barry O’Sullivan

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© 2014 Springer International Publishing Switzerland

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Amadini, R., Stuckey, P.J. (2014). Sequential Time Splitting and Bounds Communication for a Portfolio of Optimization Solvers. In: O’Sullivan, B. (eds) Principles and Practice of Constraint Programming. CP 2014. Lecture Notes in Computer Science, vol 8656. Springer, Cham. https://doi.org/10.1007/978-3-319-10428-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-10428-7_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10427-0

  • Online ISBN: 978-3-319-10428-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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