Submodular Max-SAT

Yossi Azar*, Iftah Gamzu, Ran Roth

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We introduce the submodular Max-SAT problem. This problem is a natural generalization of the classical Max-SAT problem in which the additive objective function is replaced by a submodular one. We develop a randomized linear-time 2/3-approximation algorithm for the problem. Our algorithm is applicable even for the online variant of the problem. We also establish hardness results for both the online and offline settings. Notably, for the online setting, the hardness result proves that our algorithm is best possible, while for the offline setting, the hardness result establishes a computational separation between the classical Max-SAT and the submodular Max-SAT.

Original languageEnglish
Title of host publicationAlgorithms, ESA 2011 - 19th Annual European Symposium, Proceedings
Number of pages12
StatePublished - 2011
Event19th Annual European Symposium on Algorithms, ESA 2011 - Saarbrucken, Germany
Duration: 5 Sep 20119 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6942 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th Annual European Symposium on Algorithms, ESA 2011


Dive into the research topics of 'Submodular Max-SAT'. Together they form a unique fingerprint.

Cite this