Skip to main content

Study on No-Wait Flexible Flow Shop Scheduling with Multi-objective

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11745))

Included in the following conference series:

  • 2611 Accesses

Abstract

A multi-objective flexible flow shop scheduling model is constructed inclusive of production period, total expense, and mean flow time, which is based on the characteristics of dual-resource constrained no-wait flow shop scheduling problem with unrelated parallel machines. A genetic algorithm based on Pareto is proposed to solve the multi-objective scheduling problem. Then, consider the machine and worker constraints, and unrelated parallel machines and the successive processing, the production period is given through pushing reversely from the operation. The starting time of some jobs will be delayed and the spare time of machines will be increased in order to ensure the consecutive operations of the same job. Considering three objectives, an optimal set is given, and compared to other algorithms, simulation results show that the method is effective and feasible. At last, a comparative analysis of the same case is made from no-wait flow shop scheduling and flow shop scheduling with non-consecutive operation.

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

Access this chapter

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. Aldowaisan, T.A., Allahverdi, A.: No-wait flow shop scheduling problem to minimize the number of tardy jobs. Int. J. Adv. Manuf. Technol. 61, 311–323 (2012)

    Article  Google Scholar 

  2. Engin, O., Güçlü, A.: A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems. Appl. Soft Comput. 72, 166–176 (2018)

    Article  Google Scholar 

  3. Zhao, F., Qin, S., Zhang, Y., et al.: A hybrid biogeography-based optimization with variable neighborhood search mechanism for no-wait flow shop scheduling problem. Expert Syst. Appl. 126, 321–339 (2019)

    Article  Google Scholar 

  4. Khalili, M.: A multi-objective electromagnetism algorithm for a bi-objective hybrid no-wait flow shop scheduling problem. Int. J. Adv. Manuf. Technol. 70, 1591–1601 (2014)

    Article  Google Scholar 

  5. Song, J.W., Tang, J.F.: No-wait hybrid flow shop scheduling method based on discrete particle swarm optimization. J. Syst. Simul. 22(10), 2257–2261 (2010)

    Google Scholar 

  6. Wang, B.L., Li, T.K., Sun, B.: TSP-based heuristic algorithm for permutation flow shop scheduling with limited waiting time constraints. Control Decis. 27(5), 768–772 (2012)

    MathSciNet  Google Scholar 

  7. Pan, Q.K., Wang, W.H., Zhu, J.Y.: Modified discrete particle swarm optimization algorithm for no-wait flow shop problem. Comput. Integr. Manuf. Syst. 13(6), 1127–1130 (2007)

    Google Scholar 

  8. Zhang, Q.L., Chen, Y.S.: Particle swarm optimization algorithm for bi-directional no-wait hybrid flow shop problem. Comput. Integr. Manuf. Syst. 19(10), 2503–2509 (2013)

    Google Scholar 

  9. Reddy, B.S.P., Rao, C.S.P.: A hybrid multi-objective GA for simultaneous scheduling of machines and AGVs in FMS. Int. J. Adv. Manuf. Technol. 31, 602–613 (2006)

    Article  Google Scholar 

  10. Deva Prasad, S., Rajendran, C., Krishnaiah Chetty, O.V.: A genetic algorithm approach to multi-objective scheduling in a Kanban-controlled flow shop with intermediate buffer and transport constraints. Int. J. Adv. Manuf. Technol. 29, 564–576 (2006)

    Article  Google Scholar 

  11. Huang, H.J., Lu, T.P.: Solving a multi-objective flexible job shop scheduling problem with timed Petri nets and genetic algorithm. Discrete Math. Algorithms Appl. 2(2), 221–237 (2010)

    Article  MathSciNet  Google Scholar 

  12. Tao, Z.: Study on examination center scheduling problem based on genetic algorithm and simulated annealing algorithm. Bio Technol. (23), 14354–14361(2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ze Tao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tao, Z., Liu, X. (2019). Study on No-Wait Flexible Flow Shop Scheduling with Multi-objective. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11745. Springer, Cham. https://doi.org/10.1007/978-3-030-27529-7_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27529-7_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27528-0

  • Online ISBN: 978-3-030-27529-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics