Skip to main content
SpringerLink
Log in

Balancing Assembly Lines and Matching Demand Through Worker Reallocations

  • Conference paper
  • First Online:
Modeling Decisions for Artificial Intelligence (MDAI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11144))

Abstract

Assembly lines are of great importance in most actual production systems and thus continue attracting strong research interest. We address a real industry scenario where the aim of the line is to target a production output that meets, as much as possible, a given demand forecast. To the best of our knowledge, the existing literature has not tackled this problem, and we named it the demand-driven assembly line (re)balancing problem. A mixed integer programming model is developed, solved using genetic algorithm, and tested in the straight assembly line, providing useful insights about the dynamics of worker reallocations.

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 EPUB and 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

References

  1. Azizi, N., Zolfaghari, S., Liang, M.: Modeling job rotation in manufacturing systems: the study of employee’s boredom and skill variations. Int. J. Prod. Econ. 123, 69–85 (2010)

    Article  Google Scholar 

  2. Blum, C., Miralles, C.: On solving the assembly line worker assignment and balancing problem via beam search. Comput. Oper. Res. 38, 328–339 (2011)

    Article  MathSciNet  Google Scholar 

  3. Borba, L., Ritt, M.: A heuristic and a branch-and-bound algorithm for the assembly line worker assignment and balancing problem. Comput. Oper. Res. 45, 87–96 (2014)

    Article  MathSciNet  Google Scholar 

  4. Chaves, A.A., Miralles, C., Nogueira Lorena, L.A.: Clustering search approach for the assembly line worker assignment and balancing problem. In: Elwany, M.H., Eltawil, A.B. (eds.) Proceedings of the 37th International Conference on Computers and Industrial Engineering, pp. 1469–1478 (2007)

    Google Scholar 

  5. Chaves, A.A., Nogueira Lorena, L.A., Miralles, C.: Hybrid metaheuristic for the assembly line worker assignment and balancing problem. In: Blesa, M.J., Blum, C., Di Gaspero, L., Roli, A., Sampels, M., Schaerf, A. (eds.) Proceedings of the 6th International Workshop on Hybrid Metaheuristics. LNCS, vol. 5818, pp. 1–14. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04918-7_1

    Chapter  Google Scholar 

  6. Corominas, A., Olivella, J., Pastor, R.: A model for the assignment of a set of tasks when work performance depends on experience of all tasks involved. Int. J. Prod. Econ. 126, 335–340 (2010)

    Article  Google Scholar 

  7. Givi, Z.S., Jaber, M.Y., Neumann, W.P.: Modelling worker reliability with learning and fatigue. Appl. Math. Model. 39, 5186–5199 (2015)

    Article  MathSciNet  Google Scholar 

  8. Miralles, C., García-Sabater, J.P., Andrés, C., Cardós, M.: Advantages of assembly lines in sheltered work centres for disabled: a case study. Int. J. Prod. Econ. 110, 187–197 (2007)

    Article  Google Scholar 

  9. Miralles, C., García-Sabater, J.P., Andrés, C., Cardós, M.: Branch and bound procedures for solving the assembly line worker assignment and balancing problem: application to sheltered work centres for disabled. Discret. Appl. Math. 156(3), 352–367 (2008)

    Article  MathSciNet  Google Scholar 

  10. Moreira, M.C.O., Ritt, M., Costa, A.M., Chaves, A.A.: Simple heuristics for the assembly line worker assignment and balancing problem. J. Heuristics 18, 505–524 (2012)

    Article  Google Scholar 

  11. Moreira, M.C.O., Miralles, C., Costa, A.M.: Model and heuristics for the assembly line worker integration and balancing problem. Comput. Oper. Res. 54, 64–73 (2015)

    Article  MathSciNet  Google Scholar 

  12. Moreira, M.C.O., Pastor, R., Costa, A.M., Miralles, C.: The multi-objective assembly line worker integration and balancing problem of type-2. Comput. Oper. Res. 82, 114–125 (2017)

    Article  MathSciNet  Google Scholar 

  13. Mutlu, Ö., Polat, O., Supciller, A.A.: An iterative genetic algorithm for the assembly line worker assignment and balancing problem of type-II. Comput. Oper. Res. 40, 418–426 (2013)

    Article  Google Scholar 

  14. Scholl, A.: Data of assembly line balancing problems. Technical report 16/93, Schriften zur Quantitativen Betriebswirtschaftslehre, Technische Universität Darmstadt, November 1993

    Google Scholar 

  15. Song, B.L., Wong, W.K., Fan, J.T., Chan, S.F.: A recursive operator allocation approach for assembly line-balancing optimization problem with the consideration of operator efficiency. Comput. Ind. Eng. 51, 585–608 (2006)

    Article  Google Scholar 

  16. Stall Sikora, C.G., Cantos Lopes, T., Magatão, L.: Traveling worker assembly line (re)balancing problem: Model, reduction techniques, and real case studies. Eur. J. Oper. Res. 259, 949–971 (2017)

    Article  MathSciNet  Google Scholar 

  17. Sternatz, J.: The joint line balancing and material supply problem. Int. J. Prod. Econ. 159, 304–318 (2015)

    Article  Google Scholar 

  18. Vilà, M., Pereira, J.: A branch-and-bound algorithm for assembly line worker assignment and balancing problems. Comput. Oper. Res. 44, 105–114 (2014)

    Article  MathSciNet  Google Scholar 

  19. Wilson, J.M.: Henry Ford’s just-in-time system. Int. J. Oper. Prod. Manag. 15(12), 59–75 (1995)

    Article  Google Scholar 

  20. Wilson, J.M.: Henry Ford: a just-in-time pioneer. Prod. Inven. Manag. J. 36(2), 26–31 (1996)

    Google Scholar 

  21. Wilson, J.M.: Henry Ford vs. assembly line balancing. Int. J. Prod. Res. 52(3), 757–765 (2014)

    Article  Google Scholar 

  22. Zacharia, P.T., Nearchou, A.C.: A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem. Eng. Appl. Artif. Intell. 49, 1–9 (2016)

    Article  Google Scholar 

Download references

Acknowledgment

The authors thank Ou Wei, PhD candidate at JAIST, for the technical assistance provided to run numerical experiments.

Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, 923-1292, Japan

    Randall Mauricio Pérez-Wheelock & Van-Nam Huynh

Authors
  1. Randall Mauricio Pérez-Wheelock
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Van-Nam Huynh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Randall Mauricio Pérez-Wheelock .

Editor information

Editors and Affiliations

  1. Maynooth University, Maynooth, Ireland

    Vicenç Torra

  2. Department Management Science, Tamagawa University, Tokyo, Japan

    Yasuo Narukawa

  3. University of the Balearic Islands, Palma de Mallorca, Spain

    Isabel Aguiló

  4. University of the Balearic Islands, Palma de Mallorca, Baleares, Spain

    Manuel González-Hidalgo

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pérez-Wheelock, R.M., Huynh, VN. (2018). Balancing Assembly Lines and Matching Demand Through Worker Reallocations. In: Torra, V., Narukawa, Y., Aguiló, I., González-Hidalgo, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2018. Lecture Notes in Computer Science(), vol 11144. Springer, Cham. https://doi.org/10.1007/978-3-030-00202-2_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00202-2_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00201-5

  • Online ISBN: 978-3-030-00202-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation