License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2021.56
URN: urn:nbn:de:0030-drops-153477
URL: https://drops.dagstuhl.de/opus/volltexte/2021/15347/
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Vavrille, Mathieu ; Truchet, Charlotte ; Prud'homme, Charles

Solution Sampling with Random Table Constraints

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LIPIcs-CP-2021-56.pdf (1 MB)


Abstract

Constraint programming provides generic techniques to efficiently solve combinatorial problems. In this paper, we tackle the natural question of using constraint solvers to sample combinatorial problems in a generic way. We propose an algorithm, inspired from Meel’s ApproxMC algorithm on SAT, to add hashing constraints to a CP model in order to split the search space into small cells of solutions. By sampling the solutions in the restricted search space, we can randomly generate solutions without revamping the model of the problem. We ensure the randomness by introducing a new family of hashing constraints: randomly generated tables. We implemented this solving method using the constraint solver Choco-solver. The quality of the randomness and the running time of our approach are experimentally compared to a random branching strategy. We show that our approach improves the randomness while being in the same order of magnitude in terms of running time.

BibTeX - Entry

@InProceedings{vavrille_et_al:LIPIcs.CP.2021.56,
  author =	{Vavrille, Mathieu and Truchet, Charlotte and Prud'homme, Charles},
  title =	{{Solution Sampling with Random Table Constraints}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{56:1--56:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/15347},
  URN =		{urn:nbn:de:0030-drops-153477},
  doi =		{10.4230/LIPIcs.CP.2021.56},
  annote =	{Keywords: solutions, sampling, table constraint}
}

Keywords: solutions, sampling, table constraint
Collection: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)
Issue Date: 2021
Date of publication: 15.10.2021
Supplementary Material: Software (Source Code): https://github.com/MathieuVavrille/tableSampling archived at: https://archive.softwareheritage.org/swh:1:dir:63a03fba176c348c1f9d698bda1b484957b6b5ce


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