New schemes for simplifying binary constraint satisfaction problems

Finding a solution to a Constraint Satisfaction Problem (CSP) is known to be an NP-hard task. This has motivatedthe multitude of works that have been devoted to developing techniques that simplify CSP instances before or duringtheir resolution.The present work proposes rigidly enforced schemes for s...

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Veröffentlicht in:Discrete mathematics and theoretical computer science Jg. 22 no. 1; H. Discrete Algorithms; S. 1 - 28
1. Verfasser: Naanaa, Wady
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Nancy DMTCS 01.01.2020
Discrete Mathematics & Theoretical Computer Science
Schlagworte:
[info.info-ai]computer science [cs]/artificial intelligence [cs.ai]
[info.info-cc]computer science [cs]/computational complexity [cs.cc]
Algorithms
Artificial Intelligence
Computational Complexity
Computer Science
constraint satisfaction problems
Neighborhoods
tractable csp
value merging
variable elimination
Variables
Constraint satisfaction problems
value merging
tractable CSP
variable elimination
ISSN:1365-8050, 1462-7264, 1365-8050
Online-Zugang:Volltext
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Zusammenfassung:Finding a solution to a Constraint Satisfaction Problem (CSP) is known to be an NP-hard task. This has motivatedthe multitude of works that have been devoted to developing techniques that simplify CSP instances before or duringtheir resolution.The present work proposes rigidly enforced schemes for simplifying binary CSPs that allow the narrowing of valuedomains, either via value merging or via value suppression. The proposed schemes can be viewed as parametrizedgeneralizations of two widely studied CSP simplification techniques, namely, value merging and neighbourhoodsubstitutability. Besides, we show that both schemes may be strengthened in order to allow variable elimination,which may result in more significant simplifications. This work contributes also to the theory of tractable CSPs byidentifying a new tractable class of binary CSP.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1365-8050
1462-7264
1365-8050
DOI:10.23638/DMTCS-22-1-10