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Interval Constraints with Learning: Application to Air Traffic Control

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Principles and Practice of Constraint Programming (CP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9892))

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Abstract

Lazy Clause Generation (LCG) is a learning extension of Constraint Programming that combines the power of SAT and CP. In this paper we present an extension of Lazy Clause Generation from finite domain constraints to interval constraints, that is: non-linear constraints over the reals. Because LCG solvers must be able to negate literals involved in computation, LCG for intervals must represent both open and closed intervals. This makes LCG for intervals quite different from LCG for integers. We illustrate the advantage of the technology by solving a mixed integer non-linear Air Traffic Control problem .

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Author information

Authors and Affiliations

  1. Data61, CSIRO, Melbourne, Australia

    Thibaut Feydy & Peter J. Stuckey

  2. Department of Computing and Information Systems, University of Melbourne, Melbourne, Australia

    Peter J. Stuckey

Authors
  1. Thibaut Feydy
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  2. Peter J. Stuckey
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Corresponding author

Correspondence to Thibaut Feydy .

Editor information

Editors and Affiliations

  1. University of Nice Sophia Antipolis , Sophia Antipolis, France

    Michel Rueher

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Feydy, T., Stuckey, P.J. (2016). Interval Constraints with Learning: Application to Air Traffic Control. In: Rueher, M. (eds) Principles and Practice of Constraint Programming. CP 2016. Lecture Notes in Computer Science(), vol 9892. Springer, Cham. https://doi.org/10.1007/978-3-319-44953-1_15

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  • DOI: https://doi.org/10.1007/978-3-319-44953-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44952-4

  • Online ISBN: 978-3-319-44953-1

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