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Explaining Time-Table-Edge-Finding Propagation for the Cumulative Resource Constraint

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7874))

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. Time-table-edge-finding propagators are a recent development in cumulative propagators, that combine the current resource profile (time-table) during the edge-finding propagation. The current state of the art for solving scheduling and cutting problems involving cumulative constraints are lazy clause generation solvers, i.e., constraint programming solvers incorporating nogood learning, have proved to be excellent at solving scheduling and cutting problems. For such solvers, concise and accurate explanations of the reasons for propagation are essential for strong nogood learning. In this paper, we develop a time-table-edge-finding propagator for cumulative that explains its propagations. We give results using this propagator in a lazy clause generation system on resource-constrained project scheduling problems from various standard benchmark suites. On the standard benchmark suite PSPLib, we are able to improve the lower bound of about 60% of the remaining open instances, and close 6 open instances.

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Authors and Affiliations

  1. Optimisation Research Group, National ICT Australia, and Department of Computing and Information Systems, The University of Melbourne, Victoria, 3010, Australia

    Andreas Schutt, Thibaut Feydy & Peter J. Stuckey

Authors
  1. Andreas Schutt
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  2. Thibaut Feydy
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  3. Peter J. Stuckey
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Cornell University, Ithaca, NY, USA

    Carla Gomes

  2. Thomas J. Watson Research Center, Yorktown Heights, NY, USA

    Meinolf Sellmann

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Schutt, A., Feydy, T., Stuckey, P.J. (2013). Explaining Time-Table-Edge-Finding Propagation for the Cumulative Resource Constraint. In: Gomes, C., Sellmann, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2013. Lecture Notes in Computer Science, vol 7874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38171-3_16

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  • DOI: https://doi.org/10.1007/978-3-642-38171-3_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38170-6

  • Online ISBN: 978-3-642-38171-3

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