IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v315y2024i1p63-72.html
   My bibliography  Save this article

Single machine adversarial bilevel scheduling problems

Author

Listed:
  • T’kindt, Vincent
  • Della Croce, Federico
  • Agnetis, Alessandro

Abstract

We consider single machine scheduling problems in the context of adversarial bilevel optimization where two agents, the leader and the follower, take decisions on the same jobset and the leader acts first with the aim of inducing the worst possible solution for the follower. Thus, the follower schedules the jobs in order to optimize a given criterion. The considered criteria are the total completion time, the total weighted completion time, the maximum lateness and the number of tardy jobs. We focus on adversarial bilevel scheduling with job selection and data modification. In the case with job selection, the leader selects a fixed cardinality subset of the jobs that the follower schedules next. In the case with data modification, the leader can modify some of the data (processing times, due dates, weights), given a limited budget Q. Thus, the follower schedules the set of jobs with modified data. For all the considered criteria either we provide polynomial-time algorithms or show that they can be solved in the worst-case in pseudo-polynomial time.

Suggested Citation

  • T’kindt, Vincent & Della Croce, Federico & Agnetis, Alessandro, 2024. "Single machine adversarial bilevel scheduling problems," European Journal of Operational Research, Elsevier, vol. 315(1), pages 63-72.
  • Handle: RePEc:eee:ejores:v:315:y:2024:i:1:p:63-72
    DOI: 10.1016/j.ejor.2023.11.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221723008597
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2023.11.018?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. Alessandro Agnetis & Jean-Charles Billaut & Stanisław Gawiejnowicz & Dario Pacciarelli & Ameur Soukhal, 2014. "Multiagent Scheduling," Springer Books, Springer, edition 127, number 978-3-642-41880-8, December.
    2. Alessandro Agnetis & Jean-Charles Billaut & Stanisław Gawiejnowicz & Dario Pacciarelli & Ameur Soukhal, 2014. "Multiagent Scheduling Fundamentals," Springer Books, in: Multiagent Scheduling, edition 127, chapter 0, pages 1-22, Springer.
    3. Lin, Yixun & Wang, Xiumei, 2007. "Necessary and sufficient conditions of optimality for some classical scheduling problems," European Journal of Operational Research, Elsevier, vol. 176(2), pages 809-818, January.
    4. Gerhard J. Woeginger, 2021. "The trouble with the second quantifier," 4OR, Springer, vol. 19(2), pages 157-181, June.
    5. J. Michael Moore, 1968. "An n Job, One Machine Sequencing Algorithm for Minimizing the Number of Late Jobs," Management Science, INFORMS, vol. 15(1), pages 102-109, September.
    6. Lang, Fabian & Fink, Andreas & Brandt, Tobias, 2016. "Design of automated negotiation mechanisms for decentralized heterogeneous machine scheduling," European Journal of Operational Research, Elsevier, vol. 248(1), pages 192-203.
    7. 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.
    8. Samir Abass, 2005. "Bilevel programming approach applied to the flow shop scheduling problem under fuzziness," Computational Management Science, Springer, vol. 4(4), pages 279-293, November.
    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. Shen, Zuo-Jun Max & Xie, Jingui & Zheng, Zhichao & Zhou, Han, 2023. "Dynamic scheduling with uncertain job types," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1047-1060.
    2. Zhongyi Jiang & Fangfang Chen & Xiandong Zhang, 2022. "Single-machine scheduling problems with general truncated sum-of-actual-processing-time-based learning effect," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 116-139, January.
    3. Wenhua Li & Libo Wang & Xing Chai & Hang Yuan, 2020. "Online Batch Scheduling of Simple Linear Deteriorating Jobs with Incompatible Families," Mathematics, MDPI, vol. 8(2), pages 1-12, February.
    4. Nadia Brauner & Gerd Finke & Yakov Shafransky, 2017. "Lawler’s minmax cost problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 34(1), pages 31-46, July.
    5. Marjan Akker & Han Hoogeveen & Judith Stoef, 2018. "Combining two-stage stochastic programming and recoverable robustness to minimize the number of late jobs in the case of uncertain processing times," Journal of Scheduling, Springer, vol. 21(6), pages 607-617, December.
    6. Qi Feng & Shisheng Li, 2022. "Algorithms for Multi-Customer Scheduling with Outsourcing," Mathematics, MDPI, vol. 10(9), pages 1-12, May.
    7. Oron, Daniel, 2021. "Two-agent scheduling problems under rejection budget constraints," Omega, Elsevier, vol. 102(C).
    8. Ahmadian, Mohammad Mahdi & Khatami, Mostafa & Salehipour, Amir & Cheng, T.C.E., 2021. "Four decades of research on the open-shop scheduling problem to minimize the makespan," European Journal of Operational Research, Elsevier, vol. 295(2), pages 399-426.
    9. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    10. Chen, Bo & Zhang, Xiandong, 2019. "Scheduling with time-of-use costs," European Journal of Operational Research, Elsevier, vol. 274(3), pages 900-908.
    11. Rubing Chen & Jinjiang Yuan, 2020. "Single-machine scheduling of proportional-linearly deteriorating jobs with positional due indices," 4OR, Springer, vol. 18(2), pages 177-196, June.
    12. Gudmundsson, Jens & Hougaard, Jens Leth & Platz, Trine Tornøe, 2023. "Decentralized task coordination," European Journal of Operational Research, Elsevier, vol. 304(2), pages 851-864.
    13. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    14. Alireza Amirteimoori & Simin Masrouri, 2021. "DEA-based competition strategy in the presence of undesirable products: An application to paper mills," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 5-21.
    15. Adam Kasperski & Paweł Zieliński, 2019. "Risk-averse single machine scheduling: complexity and approximation," Journal of Scheduling, Springer, vol. 22(5), pages 567-580, October.
    16. Janiak, Adam & Krysiak, Tomasz, 2012. "Scheduling jobs with values dependent on their completion times," International Journal of Production Economics, Elsevier, vol. 135(1), pages 231-241.
    17. Haokai Xie & Pu Zhao & Xudong Ji & Qun Lin & Lianguang Liu, 2019. "Expansion Planning Method of the Industrial Park Integrated Energy System Considering Regret Aversion," Energies, MDPI, vol. 12(21), pages 1-20, October.
    18. Chassein, André & Goerigk, Marc, 2018. "Variable-sized uncertainty and inverse problems in robust optimization," European Journal of Operational Research, Elsevier, vol. 264(1), pages 17-28.
    19. Detienne, Boris & Lefebvre, Henri & Malaguti, Enrico & Monaci, Michele, 2024. "Adjustable robust optimization with objective uncertainty," European Journal of Operational Research, Elsevier, vol. 312(1), pages 373-384.
    20. 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.

    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:315:y:2024:i:1:p:63-72. 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.