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Time Table Edge Finding with Energy Variables

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11494))

Abstract

Cumulative resource constraints can model scarce resources in scheduling problems or a dimension in packing and cutting problems. In order to efficiently solve such problems with a constraint programming solver, it is important to have strong and fast propagators for cumulative resource constraints. In this paper, we develop a time-table edge-finding energy propagator for cumulative constraint which can reason more strongly based on energy. We give results using this propagator in a lazy clause generation system on rectangle packing and evacuation scheduling problems. We are able to prune the search space and reduce solve time compared with a time-table or time-table edge-finding propagator.

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Authors and Affiliations

  1. University of Melbourne, Melbourne, Australia

    Moli Yang & Andreas Schutt

  2. Data61, CSIRO, Melbourne, Australia

    Andreas Schutt & Peter J. Stuckey

  3. Monash University, Melbourne, Australia

    Peter J. Stuckey

Authors
  1. Moli Yang
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  2. Andreas Schutt
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  3. Peter J. Stuckey
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Corresponding author

Correspondence to Peter J. Stuckey .

Editor information

Editors and Affiliations

  1. Ecole Polytechnique de Montréal, Montréal, QC, Canada

    Louis-Martin Rousseau

  2. University of Western Macedonia, Kozani, Greece

    Kostas Stergiou

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Yang, M., Schutt, A., Stuckey, P.J. (2019). Time Table Edge Finding with Energy Variables. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_42

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  • DOI: https://doi.org/10.1007/978-3-030-19212-9_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19211-2

  • Online ISBN: 978-3-030-19212-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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