Advertisement

The Uniform Parallel Machine Scheduling Problem: A Case Study

  • Ege Duran
  • Gizem Görgülü
  • Ayben Pınar Kuruç
  • İpek Gülhan
  • Murat Can Doğruyol
  • Hande ÖztopEmail author
  • Adalet Öner
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

In this study, the uniform parallel machine scheduling problem with non-common due dates and sequence-dependent setup times is addressed for a real-life problem in the dye house of a hood manufacturer company. The aim of this study is to create an efficient scheduling tool for the company, which minimizes lateness (earliness and tardiness) in the system and reduces the buffer stock caused by the lateness. A mathematical model is developed for the problem and optimal results are obtained for the small-sized instances. As the studied problem is NP-hard, three heuristic algorithms are also proposed to solve larger instances. The performance of the proposed algorithms is evaluated with a detailed computational experiment. Furthermore, a user-friendly decision support system (DSS) is developed using Excel VBA interface and proposed solution approaches are embedded in the DSS. The developed DSS enables users to make an efficient scheduling in very short computational time and provides the results with detailed schedule reports and Gantt charts. As this problem can be faced in various industrial areas, the proposed solution approaches can also be applied to different sectors and factories.

Keywords

Parallel machine scheduling Lateness Uniform machines Sequence-dependent setup times Heuristic algorithm Decision support system 

Notes

Acknowledgment

This work cannot be completed without the assistance of Kaan Özsümbül and Batuhan Uğuz. We are thankful for their contribution. Furthermore, we are grateful to the company for their co-operation.

References

  1. 1.
    Heady, R.B., Zhu, Z.: Minimizing the sum of job earliness and tardiness in a multimachine system. Int. J. Prod. Res. 36(6), 1619–1632 (1998)CrossRefGoogle Scholar
  2. 2.
    Radhakrishnan, S., Ventura, J.A.: Simulated annealing for parallel machine scheduling with earliness-tardiness penalties and sequence-dependent set-up times. Int. J. Prod. Res. 38(10), 2233–2252 (2000)CrossRefGoogle Scholar
  3. 3.
    Garey, M.R., Tarjan, R.E., Wilfong, G.T.: One-processor scheduling with symmetric earliness and tardiness penalties. Math. Oper. Res. 13(2), 330–348 (1988)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Kim, D.W., Kim, K.H., Jang, W., Chen, F.F.: Unrelated parallel machine scheduling with setup times using simulated annealing. Robot. Comput. Integr. Manuf. 18(3–4), 223–231 (2002)CrossRefGoogle Scholar
  5. 5.
    Lee, J.H., Yu, J.M., Lee, D.H.: A tabu search algorithm for unrelated parallel machine scheduling with sequence-and machine-dependent setups: minimizing total tardiness. Int. J. Adv. Manuf. Technol. 69(9–12), 2081–2089 (2013)CrossRefGoogle Scholar
  6. 6.
    Lee, Y.H., Pinedo, M.: Scheduling jobs on parallel machines with sequence-dependent setup times. Eur. J. Oper. Res. 100(3), 464–474 (1997)CrossRefGoogle Scholar
  7. 7.
    Hassin, R., Shani, M.: Machine scheduling with earliness, tardiness and non-execution penalties. Comput. Oper. Res. 32(3), 683–705 (2005)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Ege Duran
    • 1
  • Gizem Görgülü
    • 1
  • Ayben Pınar Kuruç
    • 1
  • İpek Gülhan
    • 1
  • Murat Can Doğruyol
    • 1
  • Hande Öztop
    • 1
    Email author
  • Adalet Öner
    • 1
  1. 1.Department of Industrial EngineeringYaşar UniversityIzmirTurkey

Personalised recommendations