Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

A two-criteria objective function flexible flowshop scheduling problem with machine eligibility constraint

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This research deals with a flexible flowshop scheduling problem with the arrival and delivery of jobs in groups and processing them individually. Each group of jobs has a specific release time. Due to the special characteristics of each job, only a specific group of machines in each stage are eligible to process that job. All jobs in a group should be delivered at the same time after processing. The objectives of the problem are the minimization of the sum of the completion time of groups on one hand and the minimization of sum of the differences between the completion time of jobs and the delivery time of the group containing that job (waiting period) on the other hand. The problem can be stated as FFc /r j , M j /irreg based on existing scheduling notations. This problem has many applications in the production and service industries such as ceramic tile manufacturing companies and restaurants. A mathematical model has been proposed to solve the problem. Since the research problem is shown to be NP-complete, a particle swarm optimization (PSO) algorithm is applied to solve the problem approximately. Based on the frequency of using local search procedure, four scenarios of PSO have been developed. The algorithms are compared by applying experimental design techniques on random test problems with different sizes. The results show that the PSO algorithm enhanced with local search for all particles has a weaker performance than the other scenarios in solving large-sized problems.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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. Graves SC (1981) A review of production scheduling. Oper Res 29(4):646–675

    Article  MathSciNet  MATH  Google Scholar 

  2. Reisman A, Kumar A, Motwani J (1997) Flowshop scheduling/sequencing research: a statistical review of the literature, 1952–1994. IEEE Trans Eng Manag 44(3):316–329

    Article  Google Scholar 

  3. Pinedo M (2008) Scheduling theory, algorithms, and systems, 3rd edn. Springer LLC, New York

    Google Scholar 

  4. Ruiz R, Maroto C (2006) A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. Eur J Oper Res 169(3):781–800

    Article  MathSciNet  MATH  Google Scholar 

  5. Salvador MS (1973) A solution to a special class of flow shop scheduling problems. In: Elmaghraby SE (ed) Symposium of the theory of scheduling and applications. Springer, Berlin, pp 83–91

    Chapter  Google Scholar 

  6. Ribas I, Leisten R, Framinan JM (2010) Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective. Comput Oper Res 37:1439–1454

    Article  MathSciNet  MATH  Google Scholar 

  7. Ruiz R, Vázquez-Rodríguez JA (2010) The hybrid flow shop scheduling problem. Eur J Oper Res 205:1–18

    Article  MATH  Google Scholar 

  8. Karimi N, Zandieh M, Karamooz HR (2010) Bi-objective group scheduling in hybrid flexible flowshop: a multi-phase approach. Expert Syst Appl 37:4024–4032

    Article  Google Scholar 

  9. Massami E, Jin ZH (2011) Optimization of container terminal unloading operations based upon multistage flexible flowshop scheduling. Appl Mech Mater 97–98:633–639

    Article  Google Scholar 

  10. Tseng CT, Liao CJ (2008) A particle swarm optimization algorithm for hybrid flowshop scheduling with multiprocessor tasks. Int J Prod Res 46(17):4655–4670

    Article  MATH  Google Scholar 

  11. Ruiz R, Serifoglu FS, Urlings T (2008) Modeling realistic hybrid flexible flowshop scheduling problems. Comput Oper Res 35(4):1151–1175

    Article  MATH  Google Scholar 

  12. Sawik T (2002) An exact approach for batch scheduling in flexible flow lines with limited intermediate buffers. Math Comput Model 36(4–5):461–471

    Article  MathSciNet  MATH  Google Scholar 

  13. Allaoui H, Artiba A (2004) Integrating simulation and optimization to schedule a hybrid flow shop with maintenance constraints. Comput Ind Eng 47(4):431–450

    Article  Google Scholar 

  14. Cheng JL, Karuno Y, Kise H (2001) A shifting bottleneck approach for a parallel machine flowshop scheduling problem. J Oper Res Soc Jpn 44(2):140–156

    MathSciNet  MATH  Google Scholar 

  15. Liao CJ, Tseng CT, Luarn P (2007) A discrete version of particle swarm optimization for flowshop scheduling problems. Comput Oper Res 34:3099–3111

    Article  MATH  Google Scholar 

  16. Hajinejad D, Salmasi N, Mokhtari R (2011) A fast hybrid particle swarm optimization algorithm for flow shop sequence dependent group scheduling problem. Scientia Iranica 18:759–764. doi:10.1016/j.scient.2011.05.023

    Article  Google Scholar 

  17. Kennedy J, Eberhart RC (1995) Particle swarm optimization. Proc IEEE Int Conf Neural Netw Piscataway IEEE 4:1942–1948

    Article  Google Scholar 

  18. Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization: an overview. Swarm Intell 1:33–57

    Article  Google Scholar 

  19. Salmasi N (2005) Multi-stage group scheduling problems with sequence dependent setups. PhD Dissertation, Oregon State University, Corvallis, USA

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

    Bita Tadayon & Nasser Salmasi

Authors
  1. Bita Tadayon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nasser Salmasi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nasser Salmasi.

Appendices

Appendix 1

Table 5 Best values of the parameters of the PSO algorithm
Full size table

Appendix 2

Table 6 ANOVA table for the experimental design model
Full size table

Appendix 3

Table 7 Result of Tukey’s test for studying G × A
Full size table

Appendix 4

Table 8 Result of Tukey’s test for studying J × A
Full size table

Appendix 5

Table 9 Result of Tukey’s test for studying G × J × A
Full size table

Appendix 6

Table 10 Result of Tukey’s test for studying G × P
Full size table

Appendix 7

Table 11 Result of Tukey’s test for studying J × P
Full size table

Appendix 8

Table 12 Result of Tukey’s test for studying G × J × P
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tadayon, B., Salmasi, N. A two-criteria objective function flexible flowshop scheduling problem with machine eligibility constraint. Int J Adv Manuf Technol 64, 1001–1015 (2013). https://doi.org/10.1007/s00170-012-4052-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-012-4052-0

Keywords

Search

Navigation