IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-3-031-24907-5_68.html
   My bibliography  Save this book chapter

Propagation and Branching Strategies for Job Shop Scheduling Minimizing the Weighted Energy Consumption

In: Operations Research Proceedings 2022

Author

Listed:
  • Andreas Bley

    (Institut für Mathematik, Universität Kassel)

  • Andreas Linß

    (Institut für Mathematik, Universität Kassel)

Abstract

We consider a job shop scheduling problem with time windows, flexible energy prices, and machines whose energy consumption depends on their operational state (offline, ramp-up, setup, processing, standby or ramp-down). The goal is to find a valid schedule that minimizes the overall energy cost. To solve this problem to optimality, we developed a branch-and-bound algorithm based on a time-indexed integer linear programming (ILP) formulation, which uses binary variables that describe blocks spanning multiple inactive periods on the machines. In this paper, we discuss the propagation and branching schemes used in that algorithm. The strategies, which are specifically tailored for energy related machine scheduling problems, primarily aim to determine and sharpen the activity profiles of the machines (and thus reduce the number of the inactive block variables) and address the workload profile of the tasks with lower priority. Computational experiments validate the efficiency of those techniques.

Suggested Citation

  • Andreas Bley & Andreas Linß, 2023. "Propagation and Branching Strategies for Job Shop Scheduling Minimizing the Weighted Energy Consumption," Lecture Notes in Operations Research, in: Oliver Grothe & Stefan Nickel & Steffen Rebennack & Oliver Stein (ed.), Operations Research Proceedings 2022, chapter 0, pages 573-580, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-24907-5_68
    DOI: 10.1007/978-3-031-24907-5_68
    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.

    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:lnopch:978-3-031-24907-5_68. 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.