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Scheduling Optional Tasks with Explanation

  • Andreas Schutt
  • Thibaut Feydy
  • Peter J. Stuckey
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8124)

Abstract

Many scheduling problems involve reasoning about tasks which may or may not actually occur, so called optional tasks. The state-of-the-art approach to modelling and solving such problems makes use of interval variables which allow a start time of \(\bot\) indicating the task does not run. In this paper we show we can model interval variables in a lazy clause generation solver, and create explaining propagators for scheduling constraints using these interval variables. Given the success of lazy clause generation on many scheduling problems, this combination appears to give a powerful new solving approach to scheduling problems with optional tasks. We demonstrate the new solving technology on well-studied flexible job-shop scheduling problems where we are able to close 36 open problems.

Keywords

Schedule Problem Interval Variable Constraint Programming Constraint Satisfaction Problem Boolean Variable 
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
    • 2
  • Thibaut Feydy
    • 1
    • 2
  • Peter J. Stuckey
    • 1
    • 2
  1. 1.Optimisation Research GroupNational ICT AustraliaAustralia
  2. 2.Department of Computing and Information SystemsThe University of MelbourneAustralia

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