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.2021.44
URN: urn:nbn:de:0030-drops-153354
URL: https://drops.dagstuhl.de/opus/volltexte/2021/15335/
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Niskanen, Andreas ; Berg, Jeremias ; Järvisalo, Matti

Enabling Incrementality in the Implicit Hitting Set Approach to MaxSAT Under Changing Weights

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LIPIcs-CP-2021-44.pdf (1 MB)


Abstract

Recent advances in solvers for the Boolean satisfiability (SAT) based optimization paradigm of maximum satisfiability (MaxSAT) have turned MaxSAT into a viable approach to finding provably optimal solutions for various types of hard optimization problems. In various types of real-world problem settings, a sequence of related optimization problems need to solved. This calls for studying ways of enabling incremental computations in MaxSAT, with the hope of speeding up the overall computation times. However, current state-of-the-art MaxSAT solvers offer no or limited forms of incrementality. In this work, we study ways of enabling incremental computations in the context of the implicit hitting set (IHS) approach to MaxSAT solving, as both one of the key MaxSAT solving approaches today and a relatively well-suited candidate for extending to incremental computations. In particular, motivated by several recent applications of MaxSAT in the context of interpretability in machine learning calling for this type of incrementality, we focus on enabling incrementality in IHS under changes to the objective function coefficients (i.e., to the weights of soft clauses). To this end, we explain to what extent different search techniques applied in IHS-based MaxSAT solving can and cannot be adapted to this incremental setting. As practical result, we develop an incremental version of an IHS MaxSAT solver, and show it provides significant runtime improvements in recent application settings which can benefit from incrementality but in which MaxSAT solvers have so-far been applied only non-incrementally, i.e., by calling a MaxSAT solver from scratch after each change to the problem instance at hand.

BibTeX - Entry

@InProceedings{niskanen_et_al:LIPIcs.CP.2021.44,
  author =	{Niskanen, Andreas and Berg, Jeremias and J\"{a}rvisalo, Matti},
  title =	{{Enabling Incrementality in the Implicit Hitting Set Approach to MaxSAT Under Changing Weights}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{44:1--44:19},
  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/2021/15335},
  URN =		{urn:nbn:de:0030-drops-153354},
  doi =		{10.4230/LIPIcs.CP.2021.44},
  annote =	{Keywords: Constraint optimization, maximum satisfiability, MaxSAT, implicit hitting set approach}
}

Keywords: Constraint optimization, maximum satisfiability, MaxSAT, implicit hitting set approach
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 and Experiment Data): https://bitbucket.org/coreo-group/incremental-maxhs/ archived at: https://archive.softwareheritage.org/swh:1:dir:9102ca0393f3004eefdd4468b8ba96346cc34476


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