IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v26y2018i1d10.1007_s10100-017-0485-8.html
   My bibliography  Save this article

Heuristic algorithms for the minmax regret flow-shop problem with interval processing times

Author

Listed:
  • Michał Ćwik

    (Wroclaw University of Science and Technology)

  • Jerzy Józefczyk

    (Wroclaw University of Science and Technology)

Abstract

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion’s value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.

Suggested Citation

  • Michał Ćwik & Jerzy Józefczyk, 2018. "Heuristic algorithms for the minmax regret flow-shop problem with interval processing times," 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. 26(1), pages 215-238, March.
    • Handle: RePEc:spr:cejnor:v:26:y:2018:i:1:d:10.1007_s10100-017-0485-8
    DOI: 10.1007/s10100-017-0485-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-017-0485-8
    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/s10100-017-0485-8?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. Kasperski, Adam & Kurpisz, Adam & Zieliński, Paweł, 2012. "Approximating a two-machine flow shop scheduling under discrete scenario uncertainty," European Journal of Operational Research, Elsevier, vol. 217(1), pages 36-43.
    2. Demirkol, Ebru & Mehta, Sanjay & Uzsoy, Reha, 1998. "Benchmarks for shop scheduling problems," European Journal of Operational Research, Elsevier, vol. 109(1), pages 137-141, August.
    3. C. T. Ng & Natalja M. Matsveichuk & Yuri N. Sotskov & T. C. Edwin Cheng, 2009. "Two-Machine Flow-Shop Minimum-Length Scheduling With Interval Processing Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(06), pages 715-734.
    4. Tamás Hajba & Zoltán Horváth, 2015. "MILP models for the optimization of real production lines," 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. 23(4), pages 899-912, December.
    5. Averbakh, Igor, 2006. "The minmax regret permutation flow-shop problem with two jobs," European Journal of Operational Research, Elsevier, vol. 169(3), pages 761-766, March.
    6. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    7. Hirshleifer, J & Riley, John G, 1979. "The Analytics of Uncertainty and Information-An Expository Survey," Journal of Economic Literature, American Economic Association, vol. 17(4), pages 1375-1421, December.
    8. 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.
    9. Jacek Błażewicz & Klaus H. Ecker & Erwin Pesch & Günter Schmidt & Jan Węglarz, 2007. "Handbook on Scheduling," International Handbooks on Information Systems, Springer, number 978-3-540-32220-7, November.
    10. Marcin Siepak & Jerzy Józefczyk, 2014. "Solution algorithms for unrelated machines minmax regret scheduling problem with interval processing times and the total flow time criterion," Annals of Operations Research, Springer, vol. 222(1), pages 517-533, November.
    11. Aissi, Hassene & Bazgan, Cristina & Vanderpooten, Daniel, 2009. "Min-max and min-max regret versions of combinatorial optimization problems: A survey," European Journal of Operational Research, Elsevier, vol. 197(2), pages 427-438, September.
    12. Roy, Bernard, 2010. "Robustness in operational research and decision aiding: A multi-faceted issue," European Journal of Operational Research, Elsevier, vol. 200(3), pages 629-638, February.
    13. 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.
    14. Kalaı¨, Rim & Lamboray, Claude & Vanderpooten, Daniel, 2012. "Lexicographic α-robustness: An alternative to min–max criteria," European Journal of Operational Research, Elsevier, vol. 220(3), pages 722-728.
    15. Kouvelis, Panagiotis & Kurawarwala, Abbas A. & Gutierrez, Genaro J., 1992. "Algorithms for robust single and multiple period layout planning for manufacturing systems," European Journal of Operational Research, Elsevier, vol. 63(2), pages 287-303, December.
    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. Levorato, Mario & Figueiredo, Rosa & Frota, Yuri, 2022. "Exact solutions for the two-machine robust flow shop with budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 300(1), pages 46-57.

    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. Levorato, Mario & Figueiredo, Rosa & Frota, Yuri, 2022. "Exact solutions for the two-machine robust flow shop with budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 300(1), pages 46-57.
    2. Da Col, Giacomo & Teppan, Erich C., 2022. "Industrial-size job shop scheduling with constraint programming," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Kasperski, Adam & Kurpisz, Adam & Zieliński, Paweł, 2012. "Approximating a two-machine flow shop scheduling under discrete scenario uncertainty," European Journal of Operational Research, Elsevier, vol. 217(1), pages 36-43.
    4. 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.
    5. Rossit, Daniel Alejandro & Tohmé, Fernando & Frutos, Mariano, 2018. "The Non-Permutation Flow-Shop scheduling problem: A literature review," Omega, Elsevier, vol. 77(C), pages 143-153.
    6. 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.
    7. Tseng, Lin-Yu & Lin, Ya-Tai, 2009. "A hybrid genetic local search algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 198(1), pages 84-92, October.
    8. 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.
    9. Jean-Paul Watson & Laura Barbulescu & L. Darrell Whitley & Adele E. Howe, 2002. "Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance," INFORMS Journal on Computing, INFORMS, vol. 14(2), pages 98-123, May.
    10. Kalaı¨, Rim & Lamboray, Claude & Vanderpooten, Daniel, 2012. "Lexicographic α-robustness: An alternative to min–max criteria," European Journal of Operational Research, Elsevier, vol. 220(3), pages 722-728.
    11. Li, Xiaoping & Wang, Qian & Wu, Cheng, 2009. "Efficient composite heuristics for total flowtime minimization in permutation flow shops," Omega, Elsevier, vol. 37(1), pages 155-164, February.
    12. Cheng, Jinliang & Steiner, George & Stephenson, Paul, 2001. "A computational study with a new algorithm for the three-machine permutation flow-shop problem with release times," European Journal of Operational Research, Elsevier, vol. 130(3), pages 559-575, May.
    13. Matthias Bultmann & Sigrid Knust & Stefan Waldherr, 2018. "Flow shop scheduling with flexible processing times," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 809-829, July.
    14. 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.
    15. Ruiz, Rubén & Maroto, Concepciøn & Alcaraz, Javier, 2006. "Two new robust genetic algorithms for the flowshop scheduling problem," Omega, Elsevier, vol. 34(5), pages 461-476, October.
    16. 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.
    17. Framinan, Jose M. & Leisten, Rainer & Ruiz-Usano, Rafael, 2002. "Efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime minimisation," European Journal of Operational Research, Elsevier, vol. 141(3), pages 559-569, September.
    18. M Haouari & T Ladhari, 2003. "A branch-and-bound-based local search method for the flow shop problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(10), pages 1076-1084, October.
    19. 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.
    20. Yannik Zeiträg & José Rui Figueira, 2023. "Automatically evolving preference-based dispatching rules for multi-objective job shop scheduling," Journal of Scheduling, Springer, vol. 26(3), pages 289-314, June.

    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:cejnor:v:26:y:2018:i:1:d:10.1007_s10100-017-0485-8. 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.