This paper addresses the solution of practical resource-constrained project scheduling problems (RCPSP). We point out that such problems often contain many, in a sense similar projects, and this characteristic can be exploited well to improve the performance of current constraint-based solvers on these problems. For that purpose, we define the straightforward but generic notion of progressive solution, in which the order of corresponding tasks of similar projects is deduced a priori. We prove that the search space can be reduced to progressive solutions. Computational experiments on two different sets of industrial problem instances are also presented.


Schedule Problem Problem Instance Product Family Precedence Constraint Constraint Satisfaction Problem 
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  1. 1.
    Aho, A.V., Hopcroft, J.E., Ullman, J.D.: The Design and Analysis of Computer Algorithms. Addison-Wesley, Reading (1974)MATHGoogle Scholar
  2. 2.
    Baptiste, Ph., Peridy, L., Pinson, E.: A Branch and Bound to Minimize the Number of Late Jobs on a Single Machine with Release Time Constraints. European Journal of Operational Research 144(1), 1–11 (2003)MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Demeulemeester, E.L., Herroelen, W.S.: Project Scheduling: A Research Handbook. Kluwer Academic Publishers, Dordrecht (2002)MATHGoogle Scholar
  4. 4.
    Hopcroft, J.E., Tarjan, R.E.: A V 2 Algorithm for Determining Isomorphism of Planar Graphs. Information Processing Letters 1, 32–34 (1971)CrossRefMATHGoogle Scholar
  5. 5.
    Jenner, B., Köbler, J., McKenzie, P., Torán, J.: Completeness Results for Graph Isomorphism. Journal of Computer and System Sciences 66(3), 549–566 (2003)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Kovács, A.: Novel Models and Algorithms for Integrated Production Planning and Scheduling. PhD Thesis, Budapest University of Technology and Economics (2005),
  7. 7.
    Kovács, A., Váncza, J.: Completable Partial Solutions in Constraint Programming and Constraint-based Scheduling. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 332–346. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Luks, E.: Isomorphism of Bounded Valence Can Be Tested in Polynomial Time. Journal of Computer and System Sciences 25, 42–46 (1982)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Mastor, A.A.: An Experimental and Comparative Evaluation of Production Line Balancing Techniques. Management Science 16, 728–746 (1970)CrossRefMATHGoogle Scholar
  10. 10.
    Nuijten, W., Bousonville, T., Focacci, F., Godard, D., Le Pape, C.: Towards an Industrial Manufacturing Scheduling Problem and Test Bed. In: Proc. of the 9th Int. Conf. on Project Management and Scheduling, pp. 162–165 (2004)Google Scholar
  11. 11.
    Petrie, K.E., Smith, B.M.: Comparison of Symmetry Breaking Methods in Constraint Programming. In: Proc. of the 5th International Workshop on Symmetry and Constraint Satisfaction Problems (2005)Google Scholar
  12. 12.
    Prestwich, S.D., Beck, J.C.: Exploiting Dominance in Three Symmetric Problems. In: Proc. of the 4th International Workshop on Symmetry and Constraint Satisfaction Problems, pp. 63–70 (2004)Google Scholar
  13. 13.
    Váncza, J., Kis, T., Kovács, A.: Aggregation – The Key to Integrating Production Planning and Scheduling. CIRP Annals – Manufacturing Technology 53(1), 377–380 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • András Kovács
    • 1
    • 2
  • József Váncza
    • 1
  1. 1.Computer and Automation Research InstituteHungarian Academy of SciencesHungary
  2. 2.Cork Constraint Computation CentreUniversity College CorkIreland

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