IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-030-22788-3_1.html
   My bibliography  Save this book chapter

Logic-Based Benders Decomposition for Large-Scale Optimization

In: Large Scale Optimization in Supply Chains and Smart Manufacturing

Author

Listed:
  • John N. Hooker

    (Carnegie Mellon University)

Abstract

Logic-based Benders decomposition (LBBD) is a substantial generalization of classical Benders decomposition that, in principle, allows the subproblem to be any optimization problem rather than specifically a linear or nonlinear programming problem. It is amenable to a wide variety of large-scale problems that decouple or otherwise simplify when certain decision variables are fixed. This chapter presents the basic theory of LBBD and explains how classical Benders decomposition is a special case. It also describes branch and check, a variant of LBBD that solves the master problem only once. It illustrates in detail how Benders cuts and subproblem relaxations can be developed for some planning and scheduling problems. It then describes the role of LBBD in three large-scale case studies. The chapter concludes with an extensive survey of the LBBD literature, organized by problem domain, to allow the reader to explore how Benders cuts have been developed for a wide range of applications.

Suggested Citation

  • John N. Hooker, 2019. "Logic-Based Benders Decomposition for Large-Scale Optimization," Springer Optimization and Its Applications, in: Jesús M. Velásquez-Bermúdez & Marzieh Khakifirooz & Mahdi Fathi (ed.), Large Scale Optimization in Supply Chains and Smart Manufacturing, pages 1-26, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-22788-3_1
    DOI: 10.1007/978-3-030-22788-3_1
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Nascimento, Paulo Jorge & Silva, Cristóvão & Antunes, Carlos Henggeler & Moniz, Samuel, 2024. "Optimal decomposition approach for solving large nesting and scheduling problems of additive manufacturing systems," European Journal of Operational Research, Elsevier, vol. 317(1), pages 92-110.
    2. Aigerim Saken & Emil Karlsson & Stephen J. Maher & Elina Rönnberg, 2023. "Computational Evaluation of Cut-Strengthening Techniques in Logic-Based Benders’ Decomposition," SN Operations Research Forum, Springer, vol. 4(3), pages 1-53, September.
    3. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    4. Ben Mohamed, Imen & Klibi, Walid & Sadykov, Ruslan & Şen, Halil & Vanderbeck, François, 2023. "The two-echelon stochastic multi-period capacitated location-routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 645-667.
    5. Caglar Gencosman, Burcu & Begen, Mehmet A., 2022. "Exact optimization and decomposition approaches for shelf space allocation," European Journal of Operational Research, Elsevier, vol. 299(2), pages 432-447.
    6. Forbes, M.A. & Harris, M.G. & Jansen, H.M. & van der Schoot, F.A. & Taimre, T., 2024. "Combining optimisation and simulation using logic-based Benders decomposition," European Journal of Operational Research, Elsevier, vol. 312(3), pages 840-854.

    More about this item

    Statistics

    Access and download statistics

    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:spochp:978-3-030-22788-3_1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.