NDLI: Resolution-based lower bounds in MaxSAT

Please wait, while we are loading the content...

Resolution-based lower bounds in MaxSAT

Content Provider	Springer Nature Link
Author	Li, Chu Min Manyà, Felip Mohamedou, uredine Ould Planes, Jordi
Copyright Year	2010
Abstract	The lower bound (LB) implemented in branch and bound MaxSAT solvers is decisive for obtaining a competitive solver. In modern solvers like MaxSatz and MiniMaxSat, the LB relies on the cooperation of the underestimation and inference components. Actually, the underestimation component of some solvers guides the application of the inference component when a conflict is reached and certain structures are found. In this paper we analyze algorithmic and logical aspects of the underestimation components that have been implemented in MaxSatz during its evolution. From an algorithmic point of view, we define novel strategies for selecting unit clauses in UP (the underestimation of LB in UP is the number of independent inconsistent subformulas detected using unit propagation), the extension of UP with failed literal detection, and a clever heuristic for guiding the application of MaxSAT resolution when UP augmented with failed literal detection is applied in the presence of cycles structures. From a logical point of view, we prove that the inconsistent subformulas detected by UP are minimally unsatisfiable, but this property does not hold if failed literal detection is added. In the presence of cycle structures in conflicts detected by UP augmented with failed literal detection, we prove that the application of MaxSAT resolution produces smaller inconsistent subformulas and, besides, generates additional clauses that may be used to improve the LB. The conducted empirical investigation indicates that the LB techniques described in this paper lead to better quality LBs.
Starting Page	456
Ending Page	484
Page Count	29
File Format	PDF
ISSN	13837133
Journal	Constraints
Volume Number	15
Issue Number	4
e-ISSN	15729354
Language	English
Publisher	Springer US
Publisher Date	2010-07-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	MaxSAT Lower bound Inference Underestimation Operations Research/Decision Theory Optimization Computing Methodologies Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Discrete Mathematics and Combinatorics Artificial Intelligence Computational Theory and Mathematics Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Reformulation based MaxSAT robustness

Improving the lower bound of simple tabular reduction

Iterative and core-guided MaxSAT solving: A survey and assessment

Lagrangian bounds from decision diagrams

Editor’s note

Boosting Haplotype Inference with Local Search

MDD propagators with explanation

Quantified maximum satisfiability

Adding laziness in BnB-ADOPT+

Resolution-based lower bounds in MaxSAT

Similar Documents

Reformulation based MaxSAT robustness

Improving the lower bound of simple tabular reduction

Iterative and core-guided MaxSAT solving: A survey and assessment

Lagrangian bounds from decision diagrams

Editor’s note

Boosting Haplotype Inference with Local Search

MDD propagators with explanation

Quantified maximum satisfiability

Adding laziness in BnB-ADOPT+

Resolution-based lower bounds in MaxSAT