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Incremental Maximum Satisfiability

Authors Andreas Niskanen , Jeremias Berg , Matti Järvisalo

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Author Details

Andreas Niskanen
  • HIIT, Department of Computer Science, University of Helsinki, Finland
Jeremias Berg
  • HIIT, Department of Computer Science, University of Helsinki, Finland
Matti Järvisalo
  • HIIT, Department of Computer Science, University of Helsinki, Finland

Funding

Work financially supported by Academy of Finland under grants 322869 and 342145.

Acknowledgements

The authors wish to thank Fahiem Bacchus, Alexey Ignatiev, Ruben Martins, and Peter Stuckey for valuable discussions on IPAMIR, and the Finnish Computing Competence Infrastructure (FCCI) for supporting this project with computational and data storage resources.

Cite As Get BibTex

Andreas Niskanen, Jeremias Berg, and Matti Järvisalo. Incremental Maximum Satisfiability. In 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 236, pp. 14:1-14:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.SAT.2022.14

Abstract

Boolean satisfiability (SAT) solvers allow for incremental computations, which is key to efficient employment of SAT solvers iteratively for developing complex decision and optimization procedures, including maximum satisfiability (MaxSAT) solvers. However, enabling incremental computations on the level of constraint optimization remains a noticeable challenge. While incremental computations have been identified to have great potential in speeding up MaxSAT-based approaches for solving various real-world optimization problems, enabling incremental computations in MaxSAT remains to most extent unexplored. In this work, we contribute towards making incremental MaxSAT solving a reality. Firstly, building on the IPASIR interface for incremental SAT solving, we propose the IPAMIR interface for implementing incremental MaxSAT solvers and for developing applications making use of incremental MaxSAT. Secondly, we expand our recent adaptation of the implicit hitting set based MaxHS MaxSAT solver to a fully-fledged incremental MaxSAT solver in terms of implementing the IPAMIR specification in full, and detail in particular how, in addition to weight changes, assumptions are enabled without losing incrementality. Thirdly, we provide further empirical evidence on the benefits of incremental MaxSAT solving under assumptions.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Combinatorial optimization
  • Theory of computation → Constraint and logic programming
Keywords
  • maximum satisfiability
  • MaxSAT
  • incremental optimization
  • API
  • implicit hitting set approach

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