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Documents authored by Niskanen, Andreas


Document
MaxSAT-Based Bi-Objective Boolean Optimization

Authors: Christoph Jabs, Jeremias Berg, Andreas Niskanen, and Matti Järvisalo

Published in: LIPIcs, Volume 236, 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)


Abstract
We explore a maximum satisfiability (MaxSAT) based approach to bi-objective optimization. Bi-objective optimization refers to the task of finding so-called Pareto-optimal solutions in terms of two objective functions. Bi-objective optimization problems naturally arise in various real-world settings. For example, in the context of learning interpretable representations, such as decision rules, from data, one wishes to balance between two objectives, the classification error and the size of the representation. Our approach is generally applicable to bi-objective optimizations which allow for propositional encodings. The approach makes heavy use of incremental Boolean satisfiability (SAT) solving and draws inspiration from modern MaxSAT solving approaches. In particular, we describe several variants of the approach which arise from different approaches to MaxSAT solving. In addition to computing a single representative solution per each point of the Pareto front, the approach allows for enumerating all Pareto-optimal solutions. We empirically compare the efficiency of the approach to recent competing approaches, showing practical benefits of our approach in the contexts of learning interpretable classification rules and bi-objective set covering.

Cite as

Christoph Jabs, Jeremias Berg, Andreas Niskanen, and Matti Järvisalo. MaxSAT-Based Bi-Objective Boolean Optimization. In 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 236, pp. 12:1-12:23, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)


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@InProceedings{jabs_et_al:LIPIcs.SAT.2022.12,
  author =	{Jabs, Christoph and Berg, Jeremias and Niskanen, Andreas and J\"{a}rvisalo, Matti},
  title =	{{MaxSAT-Based Bi-Objective Boolean Optimization}},
  booktitle =	{25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)},
  pages =	{12:1--12:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-242-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{236},
  editor =	{Meel, Kuldeep S. and Strichman, Ofer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2022.12},
  URN =		{urn:nbn:de:0030-drops-166863},
  doi =		{10.4230/LIPIcs.SAT.2022.12},
  annote =	{Keywords: Multi-objective optimization, Pareto front enumeration, bi-objective optimization, maximum satisfiability, incremental SAT}
}
Document
Incremental Maximum Satisfiability

Authors: Andreas Niskanen, Jeremias Berg, and Matti Järvisalo

Published in: LIPIcs, Volume 236, 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)


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.

Cite as

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)


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@InProceedings{niskanen_et_al:LIPIcs.SAT.2022.14,
  author =	{Niskanen, Andreas and Berg, Jeremias and J\"{a}rvisalo, Matti},
  title =	{{Incremental Maximum Satisfiability}},
  booktitle =	{25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)},
  pages =	{14:1--14:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-242-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{236},
  editor =	{Meel, Kuldeep S. and Strichman, Ofer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2022.14},
  URN =		{urn:nbn:de:0030-drops-166885},
  doi =		{10.4230/LIPIcs.SAT.2022.14},
  annote =	{Keywords: maximum satisfiability, MaxSAT, incremental optimization, API, implicit hitting set approach}
}
Document
Enabling Incrementality in the Implicit Hitting Set Approach to MaxSAT Under Changing Weights

Authors: Andreas Niskanen, Jeremias Berg, and Matti Järvisalo

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)


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.

Cite as

Andreas Niskanen, Jeremias Berg, and Matti Järvisalo. Enabling Incrementality in the Implicit Hitting Set Approach to MaxSAT Under Changing Weights. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 44:1-44:19, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)


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@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/entities/document/10.4230/LIPIcs.CP.2021.44},
  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}
}
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