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

  • Andreas Schutt
  • Thibaut Feydy
  • Peter J. Stuckey
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Constraint Programming Project Schedule Problem Early Start Time Open Instance Compulsory Part 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andreas Schutt
    • 1
  • Thibaut Feydy
    • 1
  • Peter J. Stuckey
    • 1
  1. 1.Optimisation Research Group, National ICT Australia, and Department of Computing and Information SystemsThe University of MelbourneAustralia

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