Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

A SAT Approach to Branchwidth

Published: 31 May 2019 Publication History

Abstract

Branch decomposition is a prominent method for structurally decomposing a graph, a hypergraph, or a propositional formula in conjunctive normal form. The width of a branch decomposition provides a measure of how well the object is decomposed. For many applications, it is crucial to computing a branch decomposition whose width is as small as possible. We propose an approach based on Boolean Satisfiability (SAT) to finding branch decompositions of small width. The core of our approach is an efficient SAT encoding that determines with a single SAT-call whether a given hypergraph admits a branch decomposition of a certain width. For our encoding, we propose a natural partition-based characterization of branch decompositions. The encoding size imposes a limit on the size of the given hypergraph. To break through this barrier and to scale the SAT approach to larger instances, we develop a new heuristic approach where the SAT encoding is used to locally improve a given candidate decomposition until a fixed-point is reached. This new SAT-based local improvement method scales now to instances with several thousands of vertices and edges.

References

[1]
Isolde Adler, Binh-Minh Bui-Xuan, Yuri Rabinovich, Gabriel Renault, Jan Arne Telle, and Martin Vatshelle. 2010. On the Boolean-width of a graph: Structure and applications. In Proceedings of the 36th International Workshop on Graph Theoretic Concepts in Computer Science (WG’10) (Lecture Notes in Computer Science), Dimitrios M. Thilikos (Ed.), Vol. 6410. 159--170.
[2]
Michael Alekhnovich and Alexander A. Razborov. 2002. Satisfiability, branch-width and Tseitin tautologies. In Proceedings of the 43rd Symposium on Foundations of Computer Science (FOCS’02). IEEE Computer Society, 593--603.
[3]
Fahiem Bacchus, Shannon Dalmao, and Toniann Pitassi. 2003. Algorithms and complexity results for #SAT and Bayesian inference. In Proceedings of the 44th Symposium on Foundations of Computer Science (FOCS’03). IEEE Computer Society, 340--351.
[4]
Max Bannach, Sebastian Berndt, and Thorsten Ehlers. 2017. Jdrasil: A modular library for computing tree decompositions. In Proceedings of the 16th International Symposium on Experimental Algorithms (SEA’17), Costas S. Iliopoulos, Solon P. Pissis, Simon J. Puglisi, and Rajeev Raman (Eds.), Vol. 75. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 28:1--28:21.
[5]
Jeremias Berg and Matti Järvisalo. 2014. SAT-based approaches to treewidth computation: An evaluation. In Proceedings of the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’14). IEEE Computer Society, 328--335.
[6]
Therese C. Biedl. 2014. On area-optimal planar graph drawings. In Proceedings of the 41st International Colloquium Automata, Languages, and Programming (ICALP’14) (Lecture Notes in Computer Science), Javier Esparza, Pierre Fraigniaud, Thore Husfeldt, and Elias Koutsoupias (Eds.), Vol. 8572. Springer, 198--210.
[7]
Therese C. Biedl and Martin Vatshelle. 2012. The point-set embeddability problem for plane graphs. In Proceedings of the Symposuim on Computational Geometry (SoCG’12), Tamal K. Dey and Sue Whitesides (Eds.). ACM, 41--50.
[8]
Hans Bodlander. 2016. TreewidthLIB: A benchmark for algorithms for Treewidth and related graph problems. Retrieved from http://www.staff.science.uu.nl/ bodla101/treewidthlib/.
[9]
William Cook and Paul Seymour. 2003. Tour merging via branch-decomposition. INFORMS J. Comput. 15, 3 (2003), 233--248.
[10]
Gérard Cornuéjols. 2001. Combinatorial optimization: Packing and covering. In Proceedings of the Regional Conference Series in Applied Mathematics. Society for Industrial and Applied Mathematics.
[11]
Bruno Courcelle. 1990. The monadic second-order logic of graphs. I. Recognizable sets of finite graphs. Info. Comput. 85, 1 (1990), 12--75.
[12]
Adnan Darwiche. 2009. Modeling and Reasoning with Bayesian Networks. Cambridge University Press. I--XII, 1--548 pages.
[13]
Reinhard Diestel. 2000. Graph Theory (2nd ed.). Graduate Texts in Mathematics, Vol. 173. Springer Verlag, New York.
[14]
Stefan Falkner, Marius Thomas Lindauer, and Frank Hutter. 2015. SpySMAC: Automated configuration and performance analysis of SAT solvers. In Proceedings of the 18th International Conference on Theory and Applications of Satisfiability Testing (SAT’15) (Lecture Notes in Computer Science), Marijn Heule and Sean Weaver (Eds.), Vol. 9340. Springer, 215--222.
[15]
Johannes Klaus Fichte, Neha Lodha, and Stefan Szeider. 2017. SAT-based local improvement for finding tree decompositions of small width. In Proceedings of the 20th International Conference on Theory and Applications of Satisfiability Testing (SAT’17) (Lecture Notes in Computer Science), Serge Gaspers and Toby Walsh (Eds.), Vol. 10491. Springer, 401--411.
[16]
Fedor V. Fomin, Frédéric Mazoit, and Ioan Todinca. 2009. Computing branchwidth via efficient triangulations and blocks. Discr. Appl. Math. 157, 12 (2009), 2726--2736.
[17]
Robert Ganian, Neha Lodha, Sebastian Ordyniak, and Stefan Szeider. 2019. SAT-encodings for treecut width and treedepth. In Proceedings of the 21st Workshop on Algorithm Engineering and Experiments (ALENEX’19), Stephen G. Kobourov and Henning Meyerhenke (Eds.). SIAM, 117--129.
[18]
Martin Grohe. 2008. Logic, graphs, and algorithms. In Logic and Automata: History and Perspectives (Texts in Logic and Games), Jörg Flum, Erich Grädel, and Thomas Wilke (Eds.), Vol. 2. Amsterdam University Press, 357--422.
[19]
Qian-Ping Gu and Hisao Tamaki. 2008. Optimal branch-decomposition of planar graphs in O(n<sup>3</sup>) Time. ACM Trans. Algor. 4, 3 (2008), 30:1--30:13.
[20]
Marijn Heule and Stefan Szeider. 2015. A SAT approach to clique-width. ACM Trans. Comput. Log. 16, 3 (2015), 24.
[21]
I. V. Hicks. 2002. Branchwidth heuristics. Congr. Numer. 159 (2002), 31--50.
[22]
Illya V. Hicks. 2005. Graphs, branchwidth, and tangles&excl; Oh my&excl; Networks 45, 2 (2005), 55--60.
[23]
Petr Hliněný and Sang-il Oum. 2008. Finding branch-decompositions and rank-decompositions. SIAM J. Comput. 38, 3 (2008), 1012--1032.
[24]
Kalev Kask, Andrew Gelfand, Lars Otten, and Rina Dechter. 2011. Pushing the power of stochastic greedy ordering schemes for inference in graphical models. In Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI’11), Wolfram Burgard and Dan Roth (Eds.). AAAI Press.
[25]
Neha Lodha, Sebastian Ordyniak, and Stefan Szeider. 2017. SAT-encodings for special treewidth and pathwidth. In Proceedings of the 20th International Conference on Theory and Applications of Satisfiability Testing (SAT’17) (Lecture Notes in Computer Science), Serge Gaspers and Toby Walsh (Eds.), Vol. 10491. Springer, 429--445.
[26]
Arnold Overwijk, Eelko Penninkx, and Hans L. Bodlaender. 2011. A local search algorithm for branchwidth. In Proceedings of the 37th Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM’11) (Lecture Notes in Computer Science), Ivana Cerná, Tibor Gyimóthy, Juraj Hromkovic, Keith G. Jeffery, Rastislav Královic, Marko Vukolic, and Stefan Wolf (Eds.), Vol. 6543. Springer, 444--454.
[27]
Umut Oztok and Adnan Darwiche. 2014. CV-width: A new complexity parameter for CNFs. In Proceedings of the 21st European Conference on Artificial Intelligence (ECAI’14) Including Prestigious Applications of Intelligent Systems (PAIS’14) (Frontiers in Artificial Intelligence and Applications), Torsten Schaub, Gerhard Friedrich, and Barry O’Sullivan (Eds.), Vol. 263. IOS Press, 675--680.
[28]
Neil Robertson and P. D. Seymour. 1991. Graph minors X. Obstructions to tree-decomposition. J. Comb. Theory Ser. B 52, 2 (1991), 153--190.
[29]
Neil Robertson and Paul D. Seymour. 1991. Graph minors. X. Obstructions to tree-decomposition. J. Comb. Theory, Ser. B 52, 2 (1991), 153--190.
[30]
Marko Samer and Helmut Veith. 2009. Encoding treewidth into SAT. In Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing (SAT’09) (Lecture Notes in Computer Science), Vol. 5584. Springer Verlag, 45--50.
[31]
P. D. Seymour and R. Thomas. 1994. Call routing and the ratcatcher. Combinatorica 14, 2 (1994), 217--241.
[32]
J. Cole Smith, Elif Ulusal, and Illya V. Hicks. 2012. A combinatorial optimization algorithm for solving the branchwidth problem. Comp. Opt. Appl. 51, 3 (2012), 1211--1229.
[33]
Dimitrios M. Thilikos, Maria J. Serna, and Hans L. Bodlaender. 2000. Constructive linear time algorithms for small cutwidth and carving-width. In Proceedings of the 11th International Conference on Algorithms and Computation (ISAAC’00) (Lecture Notes in Computer Science), D. T. Lee and Shang-Hua Teng (Eds.), Vol. 1969. Springer, 192--203.
[34]
Elif Ulusal. 2008. Integer Programming Models for the Branchwidth Problem. Ph.D. Dissertation. Texas A8M University.
[35]
Eric Weisstein. 2016. MathWorld online Mathematics resource. Retrieved from http://mathworld.wolfram.com.

Cited By

View all
  • (2023)Circuit minimization with QBF-based exact synthesisProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i4.25524(4087-4094)Online publication date: 7-Feb-2023
  • (2023)SAT-boosted Tabu Search for Coloring Massive GraphsACM Journal of Experimental Algorithmics10.1145/360311228(1-19)Online publication date: 30-May-2023
  • (2022)Recent Advances in Positive-Instance Driven Graph SearchingAlgorithms10.3390/a1502004215:2(42)Online publication date: 27-Jan-2022
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Computational Logic
ACM Transactions on Computational Logic  Volume 20, Issue 3
July 2019
202 pages
ISSN:1529-3785
EISSN:1557-945X
DOI:10.1145/3338853
  • Editor:
  • Orna Kupferman
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 May 2019
Accepted: 01 April 2019
Revised: 01 November 2018
Received: 01 February 2018
Published in TOCL Volume 20, Issue 3

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Branchwidth
  2. SAT encoding
  3. carving-width
  4. heuristic search

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 21 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2023)Circuit minimization with QBF-based exact synthesisProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i4.25524(4087-4094)Online publication date: 7-Feb-2023
  • (2023)SAT-boosted Tabu Search for Coloring Massive GraphsACM Journal of Experimental Algorithmics10.1145/360311228(1-19)Online publication date: 30-May-2023
  • (2022)Recent Advances in Positive-Instance Driven Graph SearchingAlgorithms10.3390/a1502004215:2(42)Online publication date: 27-Jan-2022
  • (2021)On the power and limitations of branch and cutProceedings of the 36th Computational Complexity Conference10.4230/LIPIcs.CCC.2021.6Online publication date: 20-Jul-2021
  • (2020)MaxSAT-Based Postprocessing for TreedepthPrinciples and Practice of Constraint Programming10.1007/978-3-030-58475-7_28(478-495)Online publication date: 2-Sep-2020

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media