IDEAS home Printed from https://ideas.repec.org/a/spr/flsman/v32y2020i3d10.1007_s10696-019-09363-6.html
   My bibliography  Save this article

Efficient procedures for the weighted squared tardiness permutation flowshop scheduling problem

Author

Listed:
  • Maria Raquel C. Costa

    (NORS)

  • Jorge M. S. Valente

    (Faculdade de Economia da Universidade do Porto)

  • Jeffrey E. Schaller

    (Eastern Connecticut State University)

Abstract

This paper addresses a permutation flowshop scheduling problem, with the objective of minimizing total weighted squared tardiness. The focus is on providing efficient procedures that can quickly solve medium or even large instances. Within this context, we first present multiple dispatching heuristics. These include general rules suited to various due date-related environments, heuristics developed for the problem with a linear objective function, and procedures that are suitably adapted to take the squared objective into account. Then, we describe several improvement procedures, which use one or more of three techniques. These procedures are used to improve the solution obtained by the best dispatching rule. Computational results show that the quadratic rules greatly outperform the linear counterparts, and that one of the quadratic rules is the overall best performing dispatching heuristic. The computational tests also show that all procedures significantly improve upon the initial solution. The non-dominated procedures, when considering both solution quality and runtime, are identified. The best dispatching rule, and two of the non-dominated improvement procedures, are quite efficient, and can be applied to even very large-sized problems. The remaining non-dominated improvement method can provide somewhat higher quality solutions, but it may need excessive time for extremely large instances.

Suggested Citation

  • Maria Raquel C. Costa & Jorge M. S. Valente & Jeffrey E. Schaller, 2020. "Efficient procedures for the weighted squared tardiness permutation flowshop scheduling problem," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 487-522, September.
  • Handle: RePEc:spr:flsman:v:32:y:2020:i:3:d:10.1007_s10696-019-09363-6
    DOI: 10.1007/s10696-019-09363-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10696-019-09363-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10696-019-09363-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Thomalla, Christoph S., 2001. "Job shop scheduling with alternative process plans," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 125-134, December.
    2. Ruiz, Ruben & Maroto, Concepcion, 2005. "A comprehensive review and evaluation of permutation flowshop heuristics," European Journal of Operational Research, Elsevier, vol. 165(2), pages 479-494, September.
    3. Ruiz, Ruben & Stutzle, Thomas, 2008. "An Iterated Greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1143-1159, June.
    4. Vallada, Eva & Ruiz, Rubén, 2010. "Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem," Omega, Elsevier, vol. 38(1-2), pages 57-67, February.
    5. Wayne E. Smith, 1956. "Various optimizers for single‐stage production," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 59-66, March.
    6. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    7. Ari P. J. Vepsalainen & Thomas E. Morton, 1987. "Priority Rules for Job Shops with Weighted Tardiness Costs," Management Science, INFORMS, vol. 33(8), pages 1035-1047, August.
    8. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
    9. Holsenback, J. E. & Russell, R. M. & Markland, R. E. & Philipoom, P. R., 1999. "An improved heuristic for the single-machine, weighted-tardiness problem," Omega, Elsevier, vol. 27(4), pages 485-495, August.
    10. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    11. S. S. Panwalkar & Wafik Iskander, 1977. "A Survey of Scheduling Rules," Operations Research, INFORMS, vol. 25(1), pages 45-61, February.
    12. J M Framinan & J N D Gupta & R Leisten, 2004. "A review and classification of heuristics for permutation flow-shop scheduling with makespan objective," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1243-1255, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
    2. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    3. Pessoa, Luciana S. & Andrade, Carlos E., 2018. "Heuristics for a flowshop scheduling problem with stepwise job objective function," European Journal of Operational Research, Elsevier, vol. 266(3), pages 950-962.
    4. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
    5. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
    6. Pan, Quan-Ke & Wang, Ling, 2012. "Effective heuristics for the blocking flowshop scheduling problem with makespan minimization," Omega, Elsevier, vol. 40(2), pages 218-229, April.
    7. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
    8. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
    9. Yenisey, Mehmet Mutlu & Yagmahan, Betul, 2014. "Multi-objective permutation flow shop scheduling problem: Literature review, classification and current trends," Omega, Elsevier, vol. 45(C), pages 119-135.
    10. Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.
    11. Gerardo Minella & Rubén Ruiz & Michele Ciavotta, 2008. "A Review and Evaluation of Multiobjective Algorithms for the Flowshop Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 451-471, August.
    12. Pagnozzi, Federico & Stützle, Thomas, 2019. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems," European Journal of Operational Research, Elsevier, vol. 276(2), pages 409-421.
    13. Li, Wei & Nault, Barrie R. & Ye, Honghan, 2019. "Trade-off balancing in scheduling for flow shop production and perioperative processes," European Journal of Operational Research, Elsevier, vol. 273(3), pages 817-830.
    14. Benavides, Alexander J. & Vera, Antony, 2022. "The reversibility property in a job-insertion tiebreaker for the permutational flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(2), pages 407-421.
    15. Kalczynski, Pawel J. & Kamburowski, Jerzy, 2009. "An empirical analysis of the optimality rate of flow shop heuristics," European Journal of Operational Research, Elsevier, vol. 198(1), pages 93-101, October.
    16. Framinan, Jose M. & Perez-Gonzalez, Paz, 2015. "On heuristic solutions for the stochastic flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 246(2), pages 413-420.
    17. Fernando Luis Rossi & Marcelo Seido Nagano, 2022. "Beam search-based heuristics for the mixed no-idle flowshop with total flowtime criterion," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1311-1346, December.
    18. Rad, Shahriar Farahmand & Ruiz, Rubén & Boroojerdian, Naser, 2009. "New high performing heuristics for minimizing makespan in permutation flowshops," Omega, Elsevier, vol. 37(2), pages 331-345, April.
    19. Pagnozzi, Federico & Stützle, Thomas, 2021. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems with additional constraints," Operations Research Perspectives, Elsevier, vol. 8(C).
    20. J A Vázquez-Rodríguez & G Ochoa, 2011. "On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 381-396, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:flsman:v:32:y:2020:i:3:d:10.1007_s10696-019-09363-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.