Solving weighted CSP by maintaining arc consistency

Recently, a general definition of arc consistency (AC) for soft constraint frameworks has been proposed by T. Schiex [Proc. CP-2000, Singapore, 2000, pp. 411–424]. In this paper we specialize this definition to weighted CSP and introduce two O( ed 3) enforcing algorithms. Then, we refine the definit...

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Bibliographic Details
Published inArtificial intelligence Vol. 159; no. 1; pp. 1 - 26
Main Authors Larrosa, Javier, Schiex, Thomas
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.11.2004
Subjects
Artificial intelligence
Constraint satisfaction
Local consistency
Soft constraints
Weighted CSP
Constraint satisfaction
Local consistency
Soft constraints
Weighted CSP
Online AccessGet full text
ISSN0004-3702
1872-7921
DOI10.1016/j.artint.2004.05.004

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Summary:Recently, a general definition of arc consistency (AC) for soft constraint frameworks has been proposed by T. Schiex [Proc. CP-2000, Singapore, 2000, pp. 411–424]. In this paper we specialize this definition to weighted CSP and introduce two O( ed 3) enforcing algorithms. Then, we refine the definition and introduce a stronger form of arc consistency (AC∗) along with two O( n 2 d 2+ ed 3) algorithms. As in the CSP case, an important application of AC is to combine it with search. We empirically demonstrate that a branch and bound algorithm that maintains either AC or AC∗ is a state-of-the-art general solver for weighted CSP. Our experiments cover binary Max-CSP and Max-SAT problems.
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ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2004.05.004