Diagnosing and solving over-determined constraint satisfaction problems

R.R. Bakker, F. Dikker, F. Tempelman, P.M. Wognum

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    Abstract

    Constraint relaxation is a frequently used technique for managing over-determined constraint satisfaction problems. A problem in constraint relaxation is the selection of the appropriate constraints. We show that methods developed in model-based diagnosis solve this problem. The resulting method, DOC, an abbreviation for Diagnosis of Over-determined Constraint Satisfaction Problems,
    identifies the set of least important constraints that should be relaxed to solve the remaining constraint satisfaction problem. If the solution is not acceptable for a user, DOC selects next-best sets of least-important constraints until an acceptable solution has been generated.
    The power of DOC is illustrated by a case study of scheduling the Dutch major league soccer competition. The current schedule is made using human
    insight and Operations Research methods. Using DOC, the 1992-1993 schedule has been improved by reducing the number and importance of the violated
    constraints by 56%.
    The case study revealed that efficiency improvement is a major issue in order to apply this method to large-scale over-determined scheduling and constraint
    satisfaction problems.
    Original languageEnglish
    Title of host publicationIJCAI'93
    Subtitle of host publicationProceedings of the 13th international joint conference on Artifical intelligence
    Place of PublicationChambery, France
    PublisherMorgan Kaufmann Publishers, Inc.
    Pages276-281
    Number of pages6
    Publication statusPublished - 26 Jan 1993

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