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Constraints

, Volume 19, Issue 3, pp 243–269 | Cite as

A quadratic edge-finding filtering algorithm for cumulative resource constraints

  • Roger Kameugne
  • Laure Pauline Fotso
  • Joseph Scott
  • Youcheu Ngo-Kateu
Article

Abstract

The cumulative scheduling constraint, which enforces the sharing of a finite resource by several tasks, is widely used in constraint-based scheduling applications. Propagation of the cumulative constraint can be performed by several different filtering algorithms, often used in combination. One of the most important and successful of these filtering algorithms is edge-finding. Recent work by Vilím has resulted in a 𝒪 (kn log n) algorithm for cumulative edge-finding (where n is the number of tasks and k is the number of distinct capacity requirements), as well as a new related filter, timetable edge-finding, with a complexity of 𝒪(n 2). We present a sound 𝒪(n 2) filtering algorithm for standard cumulative edge-finding, orthogonal to the work of Vilím; we also show how this algorithm’s filtering may be improved by incorporating some reasoning from extended edge-finding, with no increase in complexity. The complexity of the new algorithm does not strictly dominate previous edge-finders for small k, and it sometimes requires more iterations to reach the same fixpoint; nevertheless, results from Project Scheduling Problem Library benchmarks show that in practice this algorithm consistently outperforms earlier edge-finding filters, and remains competitive with timetable edge-finding, despite the latter algorithm’s generally stronger filtering.

Keywords

Constraint-based scheduling Edge-finding Global constraints Cumulative resource Task intervals 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Roger Kameugne
    • 1
    • 2
  • Laure Pauline Fotso
    • 3
  • Joseph Scott
    • 4
  • Youcheu Ngo-Kateu
    • 3
  1. 1.Department of Mathematics, Higher Teachers’ Training CollegeUniversity of MarouaMarouaCameroon
  2. 2.Department of Mathematics, Faculty of SciencesUniversity of Yaoundé IYaoundéCameroon
  3. 3.Department of Computer Sciences, Faculty of SciencesUniversity of Yaoundé IYaoundéCameroon
  4. 4.Department of Information Technology, Computing Science DivisionUppsala UniversityUppsalaSweden

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