LOGIC-BASED CONSTRAINT HANDLING IN RESOURCE-CONSTRAINED SCHEDULING PROBLEMS

  • J.Y. Zhang
  • J.G. Sun
  • Q.Y. Yang
Conference paper

Abstract

Resource-constrained scheduling problem is one kind of typical real-life discrete optimization problems, which is one of the strongest application areas of constraint programming. In the constraint programming toolkit ‘Mingyue’, which embed constraints in the object-oriented language C++, we design a new logic-based method for handling the constraints in the resource-constrained scheduling problem. In this paper, we propose a way of describing those constraints with the discrete-variable logic formula. Based on this model, a resolution algorithm is designed for filtering the discrete variables’ domain. Comparisons with other constraint handling approaches and related literature clearly show that our approach can describe the constraints in the high level and solve the resource-constrained scheduling problem in the logic framework.

Keywords

Lution Reso 

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REFERENCES

  1. 1.
    R. Barták (1998), On-line Guide to Constraint Programming. Charles University, Prague, http://kti.mff.cuni.cz∼bartak/constraints/.Google Scholar
  2. 2.
    M. Wallace (1994), Applying constraints for scheduling in constraint programming. In: NATO ASI Series, B. Mayoh and J. Penjaak (eds.), Springer Verlag.Google Scholar
  3. 3.
    E.P.K. Tsang (1993), Foundations of Constraint Satisfaction. San Diego, Calif.: Academic, pp. 53–63.Google Scholar
  4. 4.
    J.Y. Zhang, X. Li and J.G. Sun (2003), Research on constraint-based scheduling and its implementation. In: Proceeding of CNCC’03, Beijing, P.R. China, Tsinghua University Press, pp. 80–85.Google Scholar
  5. 5.
    J.G. Sun and J.Y. Zhang (2004), A generic mechanism for managing resource constraints in preemptive and non-preemptive scheduling. Processing of SCI’04 Conference, Orlando, USA.Google Scholar
  6. 6.
    K. Marriott and P.J. Stuckey (1998), Programming with Constraints: An Introduction. MIT Press, pp. 133–134.Google Scholar
  7. 7.
    M.C. Copper (1989), An optimal k-consistency algorithm. Artificial Intelligence, 41, pp. 89–95.CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • J.Y. Zhang
    • 1
  • J.G. Sun
    • 1
  • Q.Y. Yang
    • 1
  1. 1.College of Computer Science & TechnologyJilin UniversityChangchunP. R. China

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