Skip to main content
SpringerLink
Log in

Parallel Neuro-Tabu Search Algorithm for the Job Shop Scheduling Problem

  • Conference paper
Artificial Intelligence and Soft Computing (ICAISC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7895))

Included in the following conference series:

Abstract

We propose two parallel algorithms based on neuro-tabu search method, designed to solve the jobs shop problem of scheduling. The fist algorithm is based on independent runs of the neuro-tabu with different starting points. The second one uses sophisticated diversification method based on path-relinking methodology applied to the set of elite solutions. Proposed approaches are especially effective for the instances of large size.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alba, E.: Parallel Metaheuristics. A New Class of Algorithms. Wiley & Sons Inc. (2005)

    Google Scholar 

  2. Armentano, V.A., Scrich, C.R.: Tabu search for minimizing total tardiness in a job shop. International Journal of Production Economics 63(2), 131–140 (2000)

    Article  Google Scholar 

  3. Bożejko, W.: A new class of parallel scheduling algorithms, pp. 1–280. Wroclaw University of Technology Publishing House (2010)

    Google Scholar 

  4. Bożejko, W.: On single-walk parallelization of the job shop problem solving algorithms. Computers & Operations Research 39, 2258–2264 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bożejko, W., Uchroński: Distributed Tabu Search Algorithm for the Job Shop Problem. In: Proceedings of the 14th International Asia Pacific Conference on Computer Aided System Theory 6th to 8th Sydney, Australia, February 6-8 (2012)

    Google Scholar 

  6. Bożejko, W., Uchroński, M.: A Neuro-Tabu Search Algorithm for the Job Shop Problem. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS, vol. 6114, pp. 387–394. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  7. Bożejko, W., Uchroński, M., Wodecki, M.: Parallel Meta2heuristics for the Flexible Job Shop Problem. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS, vol. 6114, pp. 395–402. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Brandimarte, P.: Routing and scheduling in a flexible job shop by tabu search. Annals of Operations Research 41, 157–183 (1993)

    Article  MATH  Google Scholar 

  9. Brooks Jr., F.P.: The Mythical Man-Month, anniversary edition. Addison-Wesley, Reading (1995)

    Google Scholar 

  10. Bushee, D.C., Svestka, J.A.: A bi-directional scheduling approach for job shops. International Journal of Production Research 37(16), 3823–3837 (1999)

    Article  MATH  Google Scholar 

  11. Crainic, T.G., Toulouse, M., Gendreau, M.: Parallel asynchronous tabu search in multicommodity locationallocation with balancing requirements. Annals of Operations Research 63, 277–299 (1995)

    Article  Google Scholar 

  12. Dauzère-Pérès, S., Pauli, J.: An integrated approach for modeling and solving the general multiprocessor job shop scheduling problem using tabu search. Annals of Operations Research 70(3), 281–306 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  13. Diaconis, P.: Group Representations in Probability and Statistics. Lecture Notes - Mono-graph Series, vol. 11. Institute of Mathematical Statistics, Harvard University (1988)

    MATH  Google Scholar 

  14. Flynn, M.J.: Very highspeed computing systems. Proceedings of the IEEE 54, 1901–1909 (1966)

    Article  Google Scholar 

  15. Gao, J., Sun, L., Gen, M.: A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems. Computers & Operations Research 35, 2892–2907 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  16. Grabowski, J.: Generalized problems of operations sequencing in the discrete production systems, Monographs 9, Scientific Papers of the Institute of Technical Cybernetics of Wrocław Technical University (1979)

    Google Scholar 

  17. Grabowski, J., Wodecki, M.: A very fast tabu search algorithm for the job shop problem. In: Rego, C., Alidaee, B. (eds.) Adaptive Memory and Evolution, Tabu Search and Scatter Search, Kluwer Academic Publishers, Dordrecht (2005)

    Google Scholar 

  18. Hanafi, S.: On the Convergence of Tabu Search. Journal of Heuristics 7, 47–58 (2000)

    Article  Google Scholar 

  19. Holthaus, O., Rajendran, C.: Efficient jobshop dispatching rules: further developments. Production Planning and Control 11, 171–178 (2000)

    Article  Google Scholar 

  20. Hurink, E., Jurisch, B., Thole, M.: Tabu search for the job shop scheduling problem with Multi-purpose machine, Oper. Res. Spektrum 15, 205–215 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  21. Jain, A.S., Rangaswamy, B., Meeran, S.: New and stronger job-shop neighborhoods: A focus on the method of Nowicki and Smutnicki (1996). Journal of Heuristics 6(4), 457–480 (2000)

    Article  MATH  Google Scholar 

  22. Jia, H.Z., Nee, A.Y.C., Fuh, J.Y.H., Zhang, Y.F.: A modified genetic algorithm for distributed scheduling problems. International Journal of Intelligent Manufacturing 14, 351–362 (2003)

    Article  Google Scholar 

  23. Kacem, I., Hammadi, S., Borne, P.: Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems. IEEE Transactions on Systems, Man, and Cybernetics, Part C 32(1), 1–13 (2002)

    Article  Google Scholar 

  24. Pezzella, F., Morganti, G., Ciaschetti, G.: A genetic algorithm for the Flexible Job-schop Scheduling Problem. Computers & Operations Research 35, 3202–3212 (2008)

    Article  MATH  Google Scholar 

  25. Mastrolilli, M., Gambardella, L.M.: Effective neighborhood functions for the flexible job shop problem. Journal of Scheduling 3(1), 3–20 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  26. Mattfeld, D.C., Bierwirth, C.: An efficient genetic algorithm for job shop scheduling with tardiness objectives. European Journal of Operational Research 155(3), 616–630 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  27. Nowicki, E., Smutnicki, C.: An advanced tabu search algorithm for the job shop problem. Journal of Scheduling 8(2), 145–159 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  28. Nowicki, E., Smutnicki, C.: A fast taboo search algorithm for the job shop problem. Management Science 42, 797–813 (1996)

    Article  MATH  Google Scholar 

  29. Pauli, J.: A hierarchical approach for the FMS schduling problem. European Journal of Operational Research 86(1), 32–42 (1995)

    Article  Google Scholar 

  30. Pezzella, F., Merelli, E.: A tabu search method guided by shifting bottleneck for the job-shop scheduling problem. European Journal of Operational Research 120, 297–310 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  31. Pinedo, M.: Scheduling: theory, algorithms and systems. Prentice-Hall, Englewood Cliffs (2002)

    Google Scholar 

  32. Taillard, E.: Benchmarks for basic scheduling problems. European Journal of Operational Research 64, 278–285 (1993)

    Article  Google Scholar 

  33. Voß, S.: Tabu search: Applications and prospects. In: Du, D.Z., Pardalos, P.M. (eds.) Network Optimization Problems, pp. 333–353. World Scientific Publishing Co., Singapore (1993)

    Google Scholar 

  34. Wang, T.Y., Wu, K.B.: An eficient configuration generation mechanism to solve job shop scheduling problems by the simulated annealing. International Journal of Systems Science 30(5), 527–532 (1999)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Janiszewskiego 11-17, 50-372, Wrocław, Poland

    Wojciech Bożejko

  2. Wrocław Centre of Networking and Supercomputing, Wyb. Wyspiańskiego 27, 50-370, Wrocław, Poland

    Mariusz Uchroński

  3. Institute of Computer Science, University of Wrocław, Joliot-Curie 15, 50-383, Wrocław, Poland

    Mieczysław Wodecki

Authors
  1. Wojciech Bożejko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mariusz Uchroński
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mieczysław Wodecki
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bożejko, W., Uchroński, M., Wodecki, M. (2013). Parallel Neuro-Tabu Search Algorithm for the Job Shop Scheduling Problem. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38610-7_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38610-7_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38609-1

  • Online ISBN: 978-3-642-38610-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation