Skip to main content
SpringerLink
Log in

Hybrid Non-dominated Sorting Simulated Annealing Algorithm for Flexible Job Shop Scheduling Problems

  • Conference paper
ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 248))

Abstract

A new hybrid Non-dominated Sorting simulated annealing algorithm has been proposed to solve Multiobjective flexible job-shop scheduling problems (MOFJSPs). The multi objectives considered in this study are makespan, total workload of machines, workload of critical machines and total cost simultaneously. In this study, the critical or incapable machines are eliminated by non-dominated sorting of all operations and the initial solution is arrived using simulated annealing. A main feature of this proposed algorithm is its computational efficiency and simplicity in hybridization. The performance of the proposed algorithm is tested with flexible benchmark instances. The experimental results prove its performance by providing non-dominated solutions for both small and relatively larger cases in minimum computational time.

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Garey, M.R., Johnson, D.S., Sethi, R.: The complexity of flowshop and job shop scheduling. Math. Oper. Res. 1(2), 117–129 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  2. Hurink, J., Jurisch, B., Thole, M.: Tabu search for the job-shop scheduling problem with multi-purpose machines. OR-Spektrum 15(4), 205–215 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  3. Mastrolilli, M., Gambardella, L.M.: Effective neighborhood functions for the flexible job shop problem. J. Sched. 3(1), 3–20 (1996)

    Article  MathSciNet  Google Scholar 

  4. 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 Cybern, Part C 32(1), 1–13 (2002a), doi:10.1109/TSMCC.2002.1009117

    Article  Google Scholar 

  5. Kacem, I., Hammadi, S., Borne, P.: Pareto-optimality approach for flexible job-shop scheduling problems: Hybridization of evolutionary algorithms and fuzzy logic. Math. Comput. Simul. 60(3), 245–276 (2002b)

    Article  MathSciNet  MATH  Google Scholar 

  6. Tay, J.C., Wibowo, D.: An effective chromosome representation for evolving flexible job shop schedules. In: Deb, K., Tari, Z. (eds.) GECCO 2004. LNCS, vol. 3103, pp. 210–221. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Ho, N.B., Tay, J.C.: GENACE: An efficient cultural algorithm for solving the flexible job-shop problem. In: IEEE Congress on Evolutionary Computation CEC 2004, vol. 2, pp. 1759–1766. IEEE (2004), doi:10.1109/CEC.2004.1331108

    Google Scholar 

  8. Ho, N.B., Tay, J.C.: Evolving dispatching rules for solving the flexible job-shop problem. In: IEEE Congress on Evolutionary Computation, vol. 3, pp. 2848–2855. IEEE (2005), doi:10.1109/CEC.2005.1555052

    Google Scholar 

  9. Zhang, H., Gen, M.: Multistage-based genetic algorithm for flexible job-shop scheduling problem. J. Complex. Int. 11, 223–232 (2005)

    Google Scholar 

  10. Xia, W., Wu, Z.: An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems. Comput. Ind. Engg. 48(2), 409–425 (2005)

    Article  MathSciNet  Google Scholar 

  11. Gao, J., Gen, M., Sun, L., Zhao, X.: A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems. Comput. Ind. Engg. 53(1), 149–162 (2007)

    Article  MATH  Google Scholar 

  12. Gao, J., Sun, L., Gen, M.: A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems. Comput. Oper. Res. 35(9), 2892–2907 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  13. Liouane, N., Saad, I., Hammadi, S., Borne, P.: Ant systems & Local Search Optimization for flexible job shop scheduling production. Int. J. Comput. Commun. Control 2(2), 174–184 (2007)

    Google Scholar 

  14. Saidi-Mehrabad, M., Fattahi, P.: Flexible job shop scheduling with tabu search algorithms. Int. J. Adv. Manuf. Technol. 32(5-6), 563–570 (2007)

    Article  Google Scholar 

  15. Zhang, G., Shao, X., Li, P., Gao, L.: An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem. Comput. Ind. Engg. 56(4), 1309–1318 (2009)

    Article  Google Scholar 

  16. Xing, L.N., Chen, Y.W., Yang, K.W.: An efficient search method for multi-objective flexible job shop scheduling problems. J. Intell. Manuf. 20(3), 283–293 (2009)

    Article  Google Scholar 

  17. Li, J.Q., Pan, Q.K., Liang, Y.C.: An effective hybrid tabu search algorithm for multi-objective flexible job-shop scheduling problems. Comput. Ind. Engg. 59(4), 647–662 (2010)

    Article  Google Scholar 

  18. Wang, X., Gao, L., Zhang, C., Shao, X.: A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem. Int. J. Adv. Manuf. Technol. 51(5-8), 757–767 (2010)

    Article  Google Scholar 

  19. Bagheri, A., Zandieh, M., Mahdavi, I., Yazdani, M.: An artificial immune algorithm for the flexible job-shop scheduling problem. Future Gener. Comput. Syst. 26(4), 533–541 (2010)

    Article  Google Scholar 

  20. Moslehi, G., Mahnam, M.: A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. Int. J. Prod. Econ. 129, 14–22 (2011)

    Article  Google Scholar 

  21. Shivasankaran, N., Senthil Kumar, P., Nallakumarasamy, G., Venkatesh Raja, K.: A Hybrid Bubble Sorting Simulated Annealing Algorithm for Job Shop Scheduling. In: Third International Conference on Computing Communication & Networking Technologies (ICCCNT 2012), pp. 1–5. IEEE (2012), doi:10.1109/ICCCNT.2012.6395981

    Google Scholar 

  22. Shivasankaran, N., Senthil Kumar, P., Nallakumarasamy, G., Venkatesh Raja, K.: Repair Shop Job Scheduling with Parallel Operators and Multiple Constraints using Simulated Annealing. Int. J. Comput. Intell. Syst. 6(2), 223–233 (2013)

    Article  Google Scholar 

  23. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGAII. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)

    Article  Google Scholar 

  24. Frutos, M., Olivera, A.C., Tohmé, F.: A memetic algorithm based on a NSGAII scheme for the flexible job-shop scheduling problem. Ann. Oper. Res. 181(1), 745–765 (2010)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, K.S.R. College of Engineering, Tiruchengode, 637215, Tamilnadu, India

    N. Shivasankaran & P. Senthilkumar

  2. Department of Automobile Engineering, K.S.R. College of Engineering, Tiruchengode, 637215, Tamilnadu, India

    K. Venkatesh Raja

Authors
  1. N. Shivasankaran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. P. Senthilkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. Venkatesh Raja
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. Shivasankaran .

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  2. College of Engineering(A), Andhra University, Vishakapatnam, India

    P. S. Avadhani

  3. University of Hyderabad, Hyderabad, India

    Siba K. Udgata

  4. CSIR-National Institute of Oceanography, Visakhapatnam, India

    Sadasivuni Lakshminarayana

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Shivasankaran, N., Senthilkumar, P., Venkatesh Raja, K. (2014). Hybrid Non-dominated Sorting Simulated Annealing Algorithm for Flexible Job Shop Scheduling Problems. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I. Advances in Intelligent Systems and Computing, vol 248. Springer, Cham. https://doi.org/10.1007/978-3-319-03107-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03107-1_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03106-4

  • Online ISBN: 978-3-319-03107-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation