Journal of Scheduling

, Volume 19, Issue 4, pp 429–452 | Cite as

Configuration and the advantages of the shifting bottleneck procedure for optimizing the job shop total weighted tardiness scheduling problem

Article
First Online:

Abstract

This paper answers two fundamental questions concerning the usage of the shifting bottleneck (SB) procedure to optimize the criterion total weighted tardiness for the classical job shop scheduling problem. The first question is how to configure the SB procedure, as it is a divide-and-conquer method and consists of diverse subsolutions for each procedure phase. The second question is what the advantages of the SB procedure are, in comparison with other state-of-the-art approaches. To answer the first question, we evaluate the performance (i.e. the scheduling quality) and the efficiency (i.e. the computational time) of various SB variants using computational experiments and present guidelines for configuring the SB procedure. To respond to the second question, extensive computational experiments were conducted on various benchmark instances (up to 100 jobs \(\times \) 20 machines). Results show the superior performance/efficiency trade-off of the SB variants with certain configuration to local search methods. This excellent trade-off between performance and efficiency makes the SB procedure particularly promising for solving practical production scheduling problems.

Keywords

Job shop Shifting bottleneck Total weighted tardiness Production scheduling 
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Notes

Acknowledgments

This research was supported by the International Graduate School for Dynamics in Logistics (IGS) at the University of Bremen

References

  1. Adams, J., Balas, E., & Zawack, D. (1988). The shifting bottleneck procedure for job shop scheduling. Management Science, 34(3), 391–401.CrossRefGoogle Scholar
  2. Applegate, D., & Cook, W. (1991). A computational study of the job-shop scheduling problem. ORSA Journal on Computing, 3(2), 149–156.CrossRefGoogle Scholar
  3. Bellman, R. (1958). On a routing problem. Quarterly of Applied Mathematics, 16, 87–90.Google Scholar
  4. Bülbül, K. (2011). A hybrid shifting bottleneck-tabu search heuristic for the job shop total weighted tardiness problem. Computers & Operations Research, 38, 967–983.CrossRefGoogle Scholar
  5. Bülbül, K., & Kaminsky, P. (2013). A linear programming-based method for job shop scheduling. Journal of Scheduling, 16, 161–183.CrossRefGoogle Scholar
  6. Chen, J. Y., Pfund, M. E., Fowler, J. W., Montgomery, D. C., & Callarman, T. E. (2010). Robust scaling parameters for composite dispatching rules. IIE Transactions, 42(11), 842–853.CrossRefGoogle Scholar
  7. Dauzere-Peres, S. (1995). A procedure for the one-machine sequencing problem with dependent jobs. European Journal of Operational Research, 81(3), 579–589.CrossRefGoogle Scholar
  8. Dauzere-Peres, S., & Lasserre, J.-B. (1993). A modified shifting bottleneck procedure for job-shop scheduling. International Journal of Production Research, 31(4), 923–932.CrossRefGoogle Scholar
  9. Demirkol, E., Mehta, S., & Uzsoy, R. (1997). A computational study of shifting bottleneck procedures for shop scheduling problems. Journal of Heuristics, 3, 111–137.CrossRefGoogle Scholar
  10. Geiger, M. J. (2010). On heuristic search for the single machine total weighted tardiness problem—Some theoretical insights and their empirical verification. European Journal of Operational Research, 207(3), 1235–1243.CrossRefGoogle Scholar
  11. Gordon, V., Strusevich, V., & Dolgui, A. (2012). Scheduling with due date assignment under special conditions on job processing. Journal of Scheduling, 15, 447–456.CrossRefGoogle Scholar
  12. Graham, R., Lawler, E., Lenstra, J., & Kan, A. (1979). Optimization and approximation in deterministic sequencing and scheduling: A survey. Annals of Discrete Mathematics, 5, 287–326.CrossRefGoogle Scholar
  13. Hansen, P., & Mladenović, N. (2002). Developments of variable neighbourhood search. In C. C. Ribeiro & P. Hansen (Eds.), Essays and surveys in metaheuristics (pp. 415–439). Boston: Kluwer Academic Publishers.CrossRefGoogle Scholar
  14. Holthaus, O., & Rajendran, C. (2000). Efficient jobshop dispatching rules: Further developments. Production Planning & Control, 11(2), 171–178.CrossRefGoogle Scholar
  15. Holtsclaw, H. H., & Uzsoy, R. (1996). Machine criticality measures and subproblem solution procedures in shifting bottleneck methods: A computational study. The Journal of the Operational Research Society, 47(5), 666–677.CrossRefGoogle Scholar
  16. Kreipl, S. (2000). A large step random walk for minimizing total weighted tardiness in a job shop. Journal of Scheduling, 3, 125–138.CrossRefGoogle Scholar
  17. Lee, Y. H., & Pinedo, M. (1997). Scheduling jobs on parallel machines with sequence-dependent setup times. European Journal of Operational Research, 100(3), 464–474.CrossRefGoogle Scholar
  18. Mati, Y., Dauzere-Peres, S., & Lahlou, C. (2011). A general approach for optimizing regular criteria in the job-shop scheduling problem. European Journal of Operational Research, 212(1), 33–42.CrossRefGoogle Scholar
  19. Mason, S. J., Fowler, J. W., & Carlyle, W. M. (2002). A modified shifting bottleneck heuristic for minimizing total weighted tardiness in complex job shops. Journal of Scheduling, 5(3), 247–262.CrossRefGoogle Scholar
  20. Mason, S. J., Fowler, J. W., Carlyle, W. M., & Montgomery, D. C. (2005). Heuristics for minimizing total weighted tardiness in complex job shops. International Journal of Production Research, 43(10), 1943–1963.CrossRefGoogle Scholar
  21. Mladenović, N., & Hansen, P. (1997). Variable neighborhood search. Computers & Operations Research, 24, 1097–1100.CrossRefGoogle Scholar
  22. Mönch, L., Schabacker, R., Pabst, D., & Fowler, J. W. (2007). Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops. European Journal of Operational Research, 177(3), 2100–2118.CrossRefGoogle Scholar
  23. Mönch, L., & Zimmermann, J. (2007). Simulation-based assessment of machine criticality measures for a shifting bottleneck scheduling approach in complex manufacturing systems. Computers in Industry, 58(7), 644–655.CrossRefGoogle Scholar
  24. Muth, J., & Thompson, G. (1963). Industrial scheduling. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  25. Ovacikt, I. M., & Uzsoy, R. (1992). A shifting bottleneck algorithm for scheduling semiconductor testing operations. Journal of Electronics Manufacturing, 2(3), 119–134.CrossRefGoogle Scholar
  26. Ovacikt, I. M., & Uzsoy, R. (1997). Decomposition methods for complex factory scheduling problems. New York: Springer.CrossRefGoogle Scholar
  27. Pfund, M. E., Balasubramanian, H., Fowler, J. W., Mason, S. J., & Rose, O. (2008a). A multi-criteria approach for scheduling semiconductor wafer fabrication facilities. Journal of Scheduling, 11(1), 29–47.CrossRefGoogle Scholar
  28. Pfund, M. E., Fowler, J. W., Gadkari, A., & Chen, Y. (2008b). Scheduling jobs on parallel machines with setup times and ready times. Computers & Industrial Engineering, 54(4), 764–782.CrossRefGoogle Scholar
  29. Pinedo, M. (2008). Scheduling: Theory, algorithms and systems (2nd ed.). Upper Saddle River, NJ: Prentice Hall.Google Scholar
  30. Pinedo, M., & Singer, M. (1999). A shifting bottleneck heuristic for minimizing the total weighted tardiness in a job shop. Naval Research Logistics (NRL), 46(1), 1–17.CrossRefGoogle Scholar
  31. Singer, M. (2001). Decomposition methods for large job shops. Computers & Operations Research, 28(3), 193–207.CrossRefGoogle Scholar
  32. Singer, M., & Pinedo, M. (1998). A computational study of branch and bound techniques for minimizing the total weighted tardiness in job shops. IIE Transactions, 30, 109–118.Google Scholar
  33. Scholz-Reiter, B., Hildebrandt, T., & Tan, Y. (2013a). Effective and efficient scheduling of dynamic job shops—Combining the shifting bottleneck procedure with variable neighbourhood search. CIRP Annals—Manufacturing Technology, 62(1), 423–426.CrossRefGoogle Scholar
  34. Scholz-Reiter, B., Tan, Y., & Hildebrandt, T. (2013b). A computational study of shifting bottleneck procedures for job shop total weighted tardiness scheduling problems. In Proceedings of the 6th Multidisciplinary International Conference on Scheduling: Theory and Applications (pp. 437–456).Google Scholar
  35. Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 1993(64), 278–285.CrossRefGoogle Scholar
  36. Van Hentenryck, P., & Michel, L. (2004). Scheduling abstractions for local search. Lecture Notes in Computer Science, 3011, 319–334.CrossRefGoogle Scholar
  37. Vepsalainen, A. P. J., & Morton, T. E. (1987). Priority rules for job shops with weighted tardiness costs. Management Science, 33(8), 1035–1047.CrossRefGoogle Scholar
  38. Zhou, H., Cheung, W., & Leung, L. (2009). Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm. European Journal of Operational Research, 194(1), 637–649.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Yi Tan
    • 1
  • Torsten Hildebrandt
    • 1
  • Bernd Scholz-Reiter
    • 1
  1. 1.University of BremenBremenGermany

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