The SoftCumulative Constraint with Quadratic Penalty

Authors

  • Yanick Ouellet Université Laval
  • Claude-Guy Quimper Université Laval

DOI:

https://doi.org/10.1609/aaai.v36i4.20296

Keywords:

Constraint Satisfaction And Optimization (CSO)

Abstract

The Cumulative constraint greatly contributes to the success of constraint programming at solving scheduling problems. The SoftCumulative, a version of the Cumulative where overloading the resource incurs a penalty is, however, less studied. We introduce a checker and a filtering algorithm for the SoftCumulative, which are inspired by the powerful energetic reasoning rule for the Cumulative. Both algorithms can be used with classic linear penalty function, but also with a quadratic penalty function, where the penalty of overloading the resource increases quadratically with the amount of the overload. We show that these algorithms are more general than existing algorithms and vastly outperform a decomposition of the SoftCumulative in practice.

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Published

2022-06-28

How to Cite

Ouellet, Y., & Quimper, C.-G. (2022). The SoftCumulative Constraint with Quadratic Penalty. Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), 3813-3820. https://doi.org/10.1609/aaai.v36i4.20296

Issue

Section

AAAI Technical Track on Constraint Satisfaction and Optimization