Completable partial solutions in constraint programming and constraint-based scheduling

András Kovács, József Váncza

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The paper introduces the notion of freely completable partial solutions to characterize constraint satisfaction problems that have components which are relatively easy to solve and are only loosely connected to the remaining parts of the problem. Discovering such partial solutions during the solution process can result in strongly pruned search trees. We give a general definition of freely completable partial solutions, and then apply it to resource-constrained project scheduling. In this domain, we suggest a heuristic algorithm that is able to construct freely completable partial schedules. The method - together with symmetry breaking applied before search - has been successfully tested on real-life resource-constrained project scheduling problems containing up to 2000 tasks.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMark Wallace
PublisherSpringer Verlag
Pages332-346
Number of pages15
ISBN (Print)3540232419, 9783540232414
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3258
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kovács, A., & Váncza, J. (2004). Completable partial solutions in constraint programming and constraint-based scheduling. In M. Wallace (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 332-346). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3258). Springer Verlag. https://doi.org/10.1007/978-3-540-30201-8_26