Skip to main content
SpringerLink
Log in

Resource Constraints for Preemptive Job-shop Scheduling

  • Published:
Constraints Aims and scope Submit manuscript

Abstract

This paper presents an experimental study of constraint propagation algorithms for preemptive scheduling. We propose generalizations of non-preemptive constraint propagation techniques (based on timetables, on disjunctive constraints, and on edge-finding) to preemptive and “mixed” problems, i.e., problems in which some activities can be interrupted and some cannot. Another approach relies on incremental flow-based techniques. We theoretically compare these approaches and present an experimental comparison based on a branch and bound procedure for the preemptive variant of the job-shop scheduling problem. We show that both edge-finding and flow-based techniques allow the resolution of hard problem instances, including the preemptive variant of the famous FT10.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Aggoun, A. & Beldiceanu, N. (1993). Extending CHIP in Order to Solve Complex Scheduling and Placement Problems. Mathematical and Computer Modelling17:57-73.

    Google Scholar 

  2. Applegate, D. & Cook, W. (1991). A Computational Study of the Job-Shop Scheduling Problem. ORSA Journal on Computing3:149-156.

    Google Scholar 

  3. Baptiste, Ph. (1994). Constraint-Based Scheduling: Two Extensions. MSc Thesis, University of Strathclyde, Glasgow, United Kingdom.

    Google Scholar 

  4. Baptiste, Ph. & Le Pape, C. (1995a). Disjunctive Constraints for Manufacturing Scheduling: Principles and Extensions. Proc. 3rd International Conference on Computer Integrated Manufacturing, 711-718, World Scientific.

  5. Baptiste, Ph. & Le Pape, C. (1995b). A Theoretical and Experimental Comparison of Constraint Propagation Techniques for Disjunctive Scheduling. Proc. 14th International Joint Conference on Artificial Intelligence, 600-606, Morgan Kaufmann.

  6. Baptiste, Ph. (1995). Resource Constraints for Preemptive and Non-Preemptive Scheduling. MSc Thesis, University Paris VI, Paris, France.

    Google Scholar 

  7. Baptiste, Ph. & Le Pape, C. (1997). Constraint Propagation and Decomposition Techniques for Highly Disjunctive and Highly Cumulative Project Scheduling Problems. Proc. 3rd International Conference on Principles and Practice of Constraint Programming, to appear.

  8. Beck, H. (1992). Constraint Monitoring in TOSCA. Proc. AAAI Spring Symposium on Practical Approaches to Planning and Scheduling.

  9. Brucker, P. & Thiele, O. (1996). A Branch and Bound Method for the General-Shop Problem with Sequence-Dependent Setup Times. OR Spektrum18:145-161.

    Google Scholar 

  10. Burke, P. (1989). Scheduling in Dynamic Environments. PhD Thesis, University of Strathclyde, Glasgow, United Kingdom.

    Google Scholar 

  11. Burke, P. & Prosser, P. (1991). A Distributed Asynchronous System for Predictive and Reactive Scheduling. International Journal for Artificial Intelligence in Engineering6:106-124.

    Google Scholar 

  12. Carlier, J. (1984). Problèmes d'ordonnancement à contraintes de ressources: algorithmes et complexité. Thèse de Doctorat d'Etat, University Paris VI, Paris, France (in French).

    Google Scholar 

  13. Carlier, J. & Pinson, E. (1990). A Practical Use of Jackson's Preemptive Schedule for Solving the Job-Shop Problem. Annals of Operations Research26:269-287.

    Google Scholar 

  14. Carlier, J. & Pinson, E. (1994). Adjustment of Heads and Tails for the Job-Shop Problem. European Journal of Operational Research78:146-161.

    Google Scholar 

  15. Caseau, Y. & Laburthe, F. (1994). Improved CLP Scheduling with Task Intervals. Proc. 11th International Conference on Logic Programming, MIT Press.

  16. Caseau, Y. & Laburthe, F. (1995a). Improving Branch and Bound for Job-Shop Scheduling with Constraint Propagation. Proc. 8th Franco-Japanese Conference on Combinatorics and Computer Science, Springer-Verlag.

  17. Caseau, Y. & Laburthe, F. (1995b). Disjunctive Scheduling with Task Intervals. Technical Report, Ecole Normale Supérieure, Paris, France.

    Google Scholar 

  18. Caseau, Y. & Laburthe, F. (1996a). Cumulative Scheduling with Task Intervals. Proc. Joint International Conference and Symposium on Logic Programming, MIT Press.

  19. Caseau, Y. & Laburthe, F. (1996b). CLAIRE: A Parametric Tool to Generate C++ Code for Problem Solving. Working Paper, Bouygues, Direction Scientifique, Saint-Quentin-en-Yvelines, France.

    Google Scholar 

  20. Cheng, C.-C. & Smith, S. F. (1994). Generating Feasible Schedules under Complex Metric Constraints. Proc. 12th National Conference on Artificial Intelligence, 1086-1091, MIT Press.

  21. Cheng, C.-C. & Smith, S. F. (1995a). Applying Constraint Satisfaction Techniques to Job-Shop Scheduling. Technical Report, Carnegie Mellon University, Pittsburgh, Pennsylvania.

    Google Scholar 

  22. Cheng, C.-C. & Smith, S. F. (1995b). A Constraint-Posting Framework for Scheduling under Complex Constraints. Proc. AAAI-SIGMAN Workshop on Intelligent Manufacturing Systems, 64-75.

  23. Collinot, A. & Le Pape, C. (1987). Controlling Constraint Propagation. Proc. 10th International Joint Conference on Artificial Intelligence, 1032-1034, Morgan Kaufmann.

  24. Colombani, Y. (1996). Constraint Programming: An Efficient and Practical Approach to Solving the Job-Shop Problem. Proc. 2nd International Conference on Principles and Practice of Constraint Programming, 149-163, Springer-Verlag.

  25. Demeulemeester, E. (1992). Optimal Algorithms for Various Classes of Multiple Resource-Constrained Project Scheduling Problems. PhD Thesis, Katholieke Universiteit Leuven, Leuven, Belgium.

    Google Scholar 

  26. Erschler, J. (1976). Analyse sous contraintes et aide à la décision pour certains problèmes d'ordonnancement. Thèse de Doctorat d'Etat, Université Paul Sabatier, Toulouse, France (in French).

    Google Scholar 

  27. Erschler, J., Lopez, P., & Thuriot, C. (1991). Raisonnement temporel sous contraintes de ressource et problèmes d'ordonnancement. Revue d'Intelligence Artificielle5:7-32 (in French).

    Google Scholar 

  28. Esquirol, P. (1987). Règles et processus d'inférence pour l'aide à l'ordonnancement de tâches en présence de contraintes. PhD Thesis, Université Paul Sabatier, Toulouse, France (in French).

    Google Scholar 

  29. Federgruen, A. & Groenevelt, H. (1986). Preemptive Scheduling of Uniform Machines by Ordinary Network Flow Techniques. Management Science32:341-349.

    Google Scholar 

  30. Fox, B. R. (1990). Chronological and Non-Chronological Scheduling. Proc. 1st IEEE Annual Conference on Artificial Intelligence, Simulation and Planning in High Autonomy Systems.

  31. Garey, M. R. & Johnson, D. S. (1979). Computers and Intractability. A Guide to the Theory of NP-Completeness. W. H. Freeman and Company.

  32. Gondran, M. & Minoux, M. (1995). Graphes et Algorithmes. Eyrolles (in French).

  33. Kumar, V. (1992). Algorithms for Constraint Satisfaction Problems: A Survey. AI Magazine13:32-44.

    Google Scholar 

  34. Laborie, P. (1994). Planifier avec des contraintes de ressources. Proc. 2èmes rencontres des jeunes chercheurs en intelligence artificielle (in French).

  35. Le Pape, C. & Smith, S. F. (1987). Management of Temporal Constraints for Factory Scheduling. Proc. IFIP TC 8/WG 8.1Working Conference on Temporal Aspects in Information Systems, 159-170, North-Holland.

  36. Le Pape, C. (1988). Des systèmes d'ordonnancement flexibles et opportunistes. PhD Thesis, University Paris XI, Orsay, France (in French).

    Google Scholar 

  37. Le Pape, C. (1991). Constraint Propagation in Planning and Scheduling. Technical Report, Stanford University, Palo Alto, California.

    Google Scholar 

  38. Le Pape, C. (1994). Implementation of Resource Constraints in ILOG SCHEDULE: A Library for the Development of Constraint-Based Scheduling Systems. Intelligent Systems Engineering3:55-66.

    Google Scholar 

  39. Le Pape, C. (1996). An Application of Constraint Programming to a Specific Production Scheduling Problem. Belgian Journal of Operations Research, Statistics and Computer Science (to appear).

  40. Lévy, M.-L. (1996). Méthodes par décomposition temporelle et problèmes d'ordonnancement. PhD Thesis, Institut National Polytechnique de Toulouse, Toulouse, France (in French).

    Google Scholar 

  41. Lhomme, O. (1993). Consistency Techniques for Numeric CSPs. Proc. 13th International Joint Conference on Artificial Intelligence, 232-238, Morgan Kaufmann.

  42. Lock, H. C. R. (1996). An Implementation of the Cumulative Constraint. Working Paper, University of Karlsruhe, Karlsruhe, Germany.

    Google Scholar 

  43. Lopez, P. (1991). Approche énergétique pour l'ordonnancement de tâches sous contraintes de temps et de ressources. PhD Thesis, Université Paul Sabatier, Toulouse, France (in French).

    Google Scholar 

  44. Lopez, P., Erschler, J., & Esquirol, P. (1992). Ordonnancement de tâches sous contraintes: une approche énergétique. RAIRO APII 26:453-481 (in French).

    Google Scholar 

  45. Martin, P. & Shmoys, D. B. (1996). A New Approach to Computing Optimal Schedules for the Job-Shop Scheduling Problem. Proc. 5th International Conference on Integer Programming and Combinatorial Optimization.

  46. Nuijten, W. P. M. & Aarts, E. H. L. (1994). Constraint Satisfaction for Multiple Capacitated Job-Shop Scheduling. Proc. 11th European Conference on Artificial Intelligence, 635-639, John Wiley and Sons.

  47. Nuijten, W. P. M. (1994). Time and Resource Constrained Scheduling: A Constraint Satisfaction Approach. PhD Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands.

    Google Scholar 

  48. Nuijten, W. P. M. & Aarts, E. H. L. (1996). A Computational Study of Constraint Satisfaction for Multiple Capacitated Job-Shop Scheduling. European Journal of Operational Research90:269-284.

    Google Scholar 

  49. Pegman, M., Forward, N., King, B., & Teal, D. (1997). Mine Planning and Scheduling at RTZ Technical Services. Proc. 3rd International Conference and Exhibition on the Practical Application of Constraint Technology, 273-285, The Practical Application Company.

  50. Pinson, E. (1988). Le problème de job-shop. PhD Thesis, University Paris VI, Paris, France (in French).

    Google Scholar 

  51. Prosser, P. (1990). Distributed Asynchronous Scheduling. PhD Thesis, University of Strathclyde, Glasgow, United Kingdom.

    Google Scholar 

  52. Puget, J.-F. (1994). A C++ Implementation of CLP. Technical Report, ILOG S.A., Gentilly, France.

    Google Scholar 

  53. Puget, J.-F. & Leconte, M. (1995), Beyond the Glass Box: Constraints as Objects. Proc. International Symposium on Logic Programming, MIT Press.

  54. Régin, J.-C. (1994). A Filtering Algorithm for Constraints of Difference in CSPs. Proc. 12th National Conference on Artificial Intelligence, 362-367, MIT Press.

  55. Régin, J.-C. (1995). Développement d'outils algorithmiques pour l'Intelligence Artificielle. Application à la chimie organique. PhD Thesis, University Montpellier II, Montpellier, France (in French).

    Google Scholar 

  56. Régin, J.-C. (1996). Generalized Arc-Consistency for Global Cardinality Constraint” Proc. 13th National Conference on Artificial Intelligence, 209-215, MIT Press.

  57. Rit, J.-F. (1986). Propagating Temporal Constraints for Scheduling. Proc. 5th National Conference on Artificial Intelligence, 383-388, MIT Press.

  58. Smith, S. F. (1983). Exploiting Temporal Knowledge to Organize Constraints. Technical Report, Carnegie Mellon University, Pittsburgh, Pennsylvania.

    Google Scholar 

  59. Smith, S. F. (1992). Knowledge-Based Production Management: Approaches, Results and Prospects. Production Planning and Control3:350-380.

    Google Scholar 

  60. Smith, S. F. & Cheng, C.-C. (1993). Slack-Based Heuristics for Constraint Satisfaction Scheduling. Proc. 11th National Conference on Artificial Intelligence, 139-144, MIT Press.

  61. Smith, S. F. (1994). OPIS: A Methodology and Architecture for Reactive Scheduling. In: Zweben, M. & Fox, M. (editors), Intelligent Scheduling. Morgan Kaufmann.

  62. Varnier, C., Baptiste, P., & Legeard, B. (1993). Le traitement des contraintes disjonctives dans un problème d'ordonnancement: exemple du Hoist Scheduling Problem. Proc. 2èmes journées francophones de programmation logique, 343-363 (in French).

  63. Zweben, M., Davis, E., Daun, B., & Deale, M. J. (1993). Scheduling and Rescheduling with Iterative Repair. IEEE Transactions on Systems, Man, and Cybernetics23:1588-1596.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bouygues, Direction Scientifique, 1, avenue Eugène Freyssinet, 78061, Saint-Quentin-en-Yvelines, France

    Claude Le Pape

  2. UMR CNRS 6599 Heudiasyc, Université de Technologie de Compiègne, France

    Philippe Baptiste

Authors
  1. Claude Le Pape
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Philippe Baptiste
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pape, C.L., Baptiste, P. Resource Constraints for Preemptive Job-shop Scheduling. Constraints 3, 263–287 (1998). https://doi.org/10.1023/A:1009723704757

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1009723704757

Search

Navigation