IDEAS home Printed from https://ideas.repec.org/a/eee/oprepe/v12y2024ics2214716024000034.html
   My bibliography  Save this article

Pareto-optimal front generation for the bi-objective JIT scheduling problems with a piecewise linear trade-off between objectives

Author

Listed:
  • Babu, Sona
  • Girish, B.S.

Abstract

This paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted earliness and tardiness (TWET) and total flowtime (TFT) objectives in a single-machine scheduling problem (SMSP) with distinct job due dates allowing inserted idle times in the schedules. An optimal timing algorithm (OTA) is presented to generate the trade-off curve between TWET and TFT for a given sequence of jobs. The proposed method of Pareto front generation generates a Pareto-optimal front constituted of both line segments and points. Further, we employ a simple local search method to generate sequences of jobs and their respective trade-off curves, which are trimmed and merged to generate the Pareto-optimal front using the proposed method. Computational results obtained using problem instances of different sizes reveal the efficiency of the proposed OTA and the Pareto front generation method over the state-of-the-art methodologies adopted from the literature.

Suggested Citation

  • Babu, Sona & Girish, B.S., 2024. "Pareto-optimal front generation for the bi-objective JIT scheduling problems with a piecewise linear trade-off between objectives," Operations Research Perspectives, Elsevier, vol. 12(C).
  • Handle: RePEc:eee:oprepe:v:12:y:2024:i:c:s2214716024000034
    DOI: 10.1016/j.orp.2024.100299
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2214716024000034
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.orp.2024.100299?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. Kerem Bülbül & Philip Kaminsky & Candace Yano, 2004. "Flow shop scheduling with earliness, tardiness, and intermediate inventory holding costs," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(3), pages 407-445, April.
    2. Wan, Guohua & Yen, Benjamin P. -C., 2002. "Tabu search for single machine scheduling with distinct due windows and weighted earliness/tardiness penalties," European Journal of Operational Research, Elsevier, vol. 142(2), pages 271-281, October.
    3. Soylu, Banu, 2015. "Heuristic approaches for biobjective mixed 0–1 integer linear programming problems," European Journal of Operational Research, Elsevier, vol. 245(3), pages 690-703.
    4. W J Chen, 2006. "Minimizing total flow time in the single-machine scheduling problem with periodic maintenance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(4), pages 410-415, April.
    5. Guang Feng & Hoong Lau, 2008. "Efficient algorithms for machine scheduling problems with earliness and tardiness penalties," Annals of Operations Research, Springer, vol. 159(1), pages 83-95, March.
    6. Soylu, Banu, 2018. "The search-and-remove algorithm for biobjective mixed-integer linear programming problems," European Journal of Operational Research, Elsevier, vol. 268(1), pages 281-299.
    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. Soylu, Banu & Katip, Hatice, 2019. "A multiobjective hub-airport location problem for an airline network design," European Journal of Operational Research, Elsevier, vol. 277(2), pages 412-425.
    2. Nathan Adelgren & Akshay Gupte, 2022. "Branch-and-Bound for Biobjective Mixed-Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 909-933, March.
    3. Arthur Kramer & Anand Subramanian, 2019. "A unified heuristic and an annotated bibliography for a large class of earliness–tardiness scheduling problems," Journal of Scheduling, Springer, vol. 22(1), pages 21-57, February.
    4. Aritra Pal & Hadi Charkhgard, 2019. "A Feasibility Pump and Local Search Based Heuristic for Bi-Objective Pure Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 115-133, February.
    5. Yunqiang Yin & Jianyou Xu & T. C. E. Cheng & Chin‐Chia Wu & Du‐Juan Wang, 2016. "Approximation schemes for single‐machine scheduling with a fixed maintenance activity to minimize the total amount of late work," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(2), pages 172-183, March.
    6. Konur, Dinçer & Campbell, James F. & Monfared, Sepideh A., 2017. "Economic and environmental considerations in a stochastic inventory control model with order splitting under different delivery schedules among suppliers," Omega, Elsevier, vol. 71(C), pages 46-65.
    7. Hanane Krim & Rachid Benmansour & David Duvivier & Daoud Aït-Kadi & Said Hanafi, 2020. "Heuristics for the single machine weighted sum of completion times scheduling problem with periodic maintenance," Computational Optimization and Applications, Springer, vol. 75(1), pages 291-320, January.
    8. Imed Kacem, 2009. "Approximation algorithms for the makespan minimization with positive tails on a single machine with a fixed non-availability interval," Journal of Combinatorial Optimization, Springer, vol. 17(2), pages 117-133, February.
    9. Sourd, Francis, 2005. "Punctuality and idleness in just-in-time scheduling," European Journal of Operational Research, Elsevier, vol. 167(3), pages 739-751, December.
    10. Hendel, Yann & Sourd, Francis, 2006. "Efficient neighborhood search for the one-machine earliness-tardiness scheduling problem," European Journal of Operational Research, Elsevier, vol. 173(1), pages 108-119, August.
    11. Shirvani, Nargess & Ruiz, Rubén & Shadrokh, Shahram, 2014. "Cyclic scheduling of perishable products in parallel machine with release dates, due dates and deadlines," International Journal of Production Economics, Elsevier, vol. 156(C), pages 1-12.
    12. Simon Thevenin & Nicolas Zufferey & Marino Widmer, 2016. "Order acceptance and scheduling with earliness and tardiness penalties," Journal of Heuristics, Springer, vol. 22(6), pages 849-890, December.
    13. Yıldız, Gazi Bilal & Soylu, Banu, 2019. "A multiobjective post-sales guarantee and repair services network design problem," International Journal of Production Economics, Elsevier, vol. 216(C), pages 305-320.
    14. Wan, Guohua & Yen, Benjamin P.-C., 2009. "Single machine scheduling to minimize total weighted earliness subject to minimal number of tardy jobs," European Journal of Operational Research, Elsevier, vol. 195(1), pages 89-97, May.
    15. Chen, Wen-Jinn, 2009. "Minimizing number of tardy jobs on a single machine subject to periodic maintenance," Omega, Elsevier, vol. 37(3), pages 591-599, June.
    16. Guillermo Cabrera-Guerrero & Matthias Ehrgott & Andrew J. Mason & Andrea Raith, 2022. "Bi-objective optimisation over a set of convex sub-problems," Annals of Operations Research, Springer, vol. 319(2), pages 1507-1532, December.
    17. Fritz Bökler & Sophie N. Parragh & Markus Sinnl & Fabien Tricoire, 2024. "An outer approximation algorithm for generating the Edgeworth–Pareto hull of multi-objective mixed-integer linear programming problems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 100(1), pages 263-290, August.
    18. F. Rodriguez & C. Blum & C. García-Martínez & M. Lozano, 2012. "GRASP with path-relinking for the non-identical parallel machine scheduling problem with minimising total weighted completion times," Annals of Operations Research, Springer, vol. 201(1), pages 383-401, December.
    19. Diego Pecin & Ian Herszterg & Tyler Perini & Natashia Boland & Martin Savelsbergh, 2024. "A fast and robust algorithm for solving biobjective mixed integer programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 100(1), pages 221-262, August.
    20. Janiak, Adam & Janiak, Władysław A. & Krysiak, Tomasz & Kwiatkowski, Tomasz, 2015. "A survey on scheduling problems with due windows," European Journal of Operational Research, Elsevier, vol. 242(2), pages 347-357.

    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:oprepe:v:12:y:2024:i:c:s2214716024000034. 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.journals.elsevier.com/operations-research-perspectives .

    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.