IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v245y2015i1p35-45.html
   My bibliography  Save this article

Scatter search with path relinking for the flexible job shop scheduling problem

Author

Listed:
  • González, Miguel A.
  • Vela, Camino R.
  • Varela, Ramiro

Abstract

The flexible job shop scheduling is a challenging problem due to its high complexity and the huge number of applications it has in real production environments. In this paper, we propose effective neighborhood structures for this problem, including feasibility and non improving conditions, as well as procedures for fast estimation of the neighbors quality. These neighborhoods are embedded into a scatter search algorithm which uses tabu search and path relinking in its core. To develop these metaheuristics we define a novel dissimilarity measure, which deals with flexibility. We conducted an experimental study to analyze the proposed algorithm and to compare it with the state of the art on standard benchmarks. In this study, our algorithm compared favorably to other methods and established new upper bounds for a number of instances.

Suggested Citation

  • González, Miguel A. & Vela, Camino R. & Varela, Ramiro, 2015. "Scatter search with path relinking for the flexible job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 245(1), pages 35-45.
    • Handle: RePEc:eee:ejores:v:245:y:2015:i:1:p:35-45
    DOI: 10.1016/j.ejor.2015.02.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715001721
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.02.052?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. Sels, Veronique & Craeymeersch, Kjeld & Vanhoucke, Mario, 2011. "A hybrid single and dual population search procedure for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 215(3), pages 512-523, December.
    2. Marti, Rafael & Laguna, Manuel & Glover, Fred, 2006. "Principles of scatter search," European Journal of Operational Research, Elsevier, vol. 169(2), pages 359-372, March.
    3. Mati, Yazid & Dauzère-Pérès, Stèphane & Lahlou, Chams, 2011. "A general approach for optimizing regular criteria in the job-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 212(1), pages 33-42, July.
    4. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 2006. "Some aspects of scatter search in the flow-shop problem," European Journal of Operational Research, Elsevier, vol. 169(2), pages 654-666, March.
    5. Eugeniusz Nowicki & Czeslaw Smutnicki, 1996. "A Fast Taboo Search Algorithm for the Job Shop Problem," Management Science, INFORMS, vol. 42(6), pages 797-813, June.
    6. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    7. Ho, Nhu Binh & Tay, Joc Cing & Lai, Edmund M.-K., 2007. "An effective architecture for learning and evolving flexible job-shop schedules," European Journal of Operational Research, Elsevier, vol. 179(2), pages 316-333, June.
    8. Stéphane Dauzère-Pérès & Jan Paulli, 1997. "An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search," Annals of Operations Research, Springer, vol. 70(0), pages 281-306, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wieslaw Kubiak & Yanling Feng & Guo Li & Suresh P. Sethi & Chelliah Sriskandarajah, 2020. "Efficient algorithms for flexible job shop scheduling with parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 272-288, June.
    2. Lunardi, Willian T. & Birgin, Ernesto G. & Ronconi, Débora P. & Voos, Holger, 2021. "Metaheuristics for the online printing shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 293(2), pages 419-441.
    3. Gregory A. Kasapidis & Stéphane Dauzère‐Pérès & Dimitris C. Paraskevopoulos & Panagiotis P. Repoussis & Christos D. Tarantilis, 2023. "On the multiresource flexible job‐shop scheduling problem with arbitrary precedence graphs," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2322-2330, July.
    4. Jiae Zhang & Jianjun Yang, 2016. "Flexible job-shop scheduling with flexible workdays, preemption, overlapping in operations and satisfaction criteria: an industrial application," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4894-4918, August.
    5. Mangesh Gharote & Rahul Patil & Sachin Lodha, 2017. "Scatter search for trainees to software project requirements stable allocation," Journal of Heuristics, Springer, vol. 23(4), pages 257-283, August.
    6. Gregory A. Kasapidis & Dimitris C. Paraskevopoulos & Panagiotis P. Repoussis & Christos D. Tarantilis, 2021. "Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4044-4068, November.
    7. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.

    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. Shen, Liji & Dauzère-Pérès, Stéphane & Neufeld, Janis S., 2018. "Solving the flexible job shop scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 265(2), pages 503-516.
    2. Shen, Liji & Buscher, Udo, 2012. "Solving the serial batching problem in job shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 14-26.
    3. Tamssaouet, Karim & Dauzère-Pérès, Stéphane, 2023. "A general efficient neighborhood structure framework for the job-shop and flexible job-shop scheduling problems," European Journal of Operational Research, Elsevier, vol. 311(2), pages 455-471.
    4. Gregory A. Kasapidis & Dimitris C. Paraskevopoulos & Panagiotis P. Repoussis & Christos D. Tarantilis, 2021. "Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4044-4068, November.
    5. Shen, Liji & Dauzère-Pérès, Stéphane & Maecker, Söhnke, 2023. "Energy cost efficient scheduling in flexible job-shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 310(3), pages 992-1016.
    6. 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.
    7. Chong Peng & Guanglin Wu & T Warren Liao & Hedong Wang, 2019. "Research on multi-agent genetic algorithm based on tabu search for the job shop scheduling problem," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-19, September.
    8. Rossi, Andrea, 2014. "Flexible job shop scheduling with sequence-dependent setup and transportation times by ant colony with reinforced pheromone relationships," International Journal of Production Economics, Elsevier, vol. 153(C), pages 253-267.
    9. Alper Türkyılmaz & Özlem Şenvar & İrem Ünal & Serol Bulkan, 2020. "A research survey: heuristic approaches for solving multi objective flexible job shop problems," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1949-1983, December.
    10. Bürgy, Reinhard & Bülbül, Kerem, 2018. "The job shop scheduling problem with convex costs," European Journal of Operational Research, Elsevier, vol. 268(1), pages 82-100.
    11. Nicolás Álvarez-Gil & Rafael Rosillo & David de la Fuente & Raúl Pino, 2021. "A discrete firefly algorithm for solving the flexible job-shop scheduling problem in a make-to-order manufacturing system," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(4), pages 1353-1374, December.
    12. J. Christopher Beck & T. K. Feng & Jean-Paul Watson, 2011. "Combining Constraint Programming and Local Search for Job-Shop Scheduling," INFORMS Journal on Computing, INFORMS, vol. 23(1), pages 1-14, February.
    13. Julien Autuori & Faicel Hnaien & Farouk Yalaoui, 2016. "A mapping technique for better solution exploration: NSGA-II adaptation," Journal of Heuristics, Springer, vol. 22(1), pages 89-123, February.
    14. De Giovanni, L. & Pezzella, F., 2010. "An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem," European Journal of Operational Research, Elsevier, vol. 200(2), pages 395-408, January.
    15. Quadt, Daniel & Kuhn, Heinrich, 2007. "A taxonomy of flexible flow line scheduling procedures," European Journal of Operational Research, Elsevier, vol. 178(3), pages 686-698, May.
    16. Vilcot, Geoffrey & Billaut, Jean-Charles, 2008. "A tabu search and a genetic algorithm for solving a bicriteria general job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 190(2), pages 398-411, October.
    17. T. C. E. Cheng & Bo Peng & Zhipeng Lü, 2016. "A hybrid evolutionary algorithm to solve the job shop scheduling problem," Annals of Operations Research, Springer, vol. 242(2), pages 223-237, July.
    18. Drótos, Márton & Erdos, Gábor & Kis, Tamás, 2009. "Computing lower and upper bounds for a large-scale industrial job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 296-306, August.
    19. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.
    20. Reinhard Bürgy, 2017. "A neighborhood for complex job shop scheduling problems with regular objectives," Journal of Scheduling, Springer, vol. 20(4), pages 391-422, August.

    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:eee:ejores:v:245:y:2015:i:1:p:35-45. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.