IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-13382-4_12.html
   My bibliography  Save this book chapter

Design of Scheduling Algorithms

In: Behavioral Operations in Planning and Scheduling

Author

Listed:
  • Jan Riezebos

    (University of Groningen)

  • Jean-Michel Hoc

    (University of Technology of Compiègne)

  • Nasser Mebarki

    (University of Nantes)

  • Christos Dimopoulos

    (European University Cyprus)

  • Wout Wezel

    (University of Groningen)

  • Guillaume Pinot

    (University of Technology of Compiègne)

Abstract

The accomplishment of a manufacturing company’s objectives is strongly connected to the efficient solution of scheduling problems that are faced in the production environment. Numerous methods for the solution of these problems have been published. However, very few of them have been adopted by manufacturing companies. This chapter suggests that the basic reason behind this imbalance is the inadequate representation of the scheduling process when designing decision support systems. Hence, the algorithms that are designed and included in these systems might not reflect the problems that actually have to be solved. The relevance of algorithmic design can be improved by using a more complete representation of the scheduling process, which would be highly relevant for increasing the adoption rate of new support systems. The main contribution of the chapter concerns the development of a theoretical framework for the design of scheduling decision support systems. This framework is based on an interdisciplinary approach that integrates insights from cognitive psychology, computer science, and operations management. The use of this framework implies that the design of a decision support system should start with an examination of the human, organizational, and technical characteristics of the scheduling situation that has to be supported. This information can be obtained and analyzed using appropriate methodologies such as hierarchical task analysis, cognitive task analysis and cognitive work analysis as well as other methodologies, such as interviews, observations, context diagrams, and data flow diagrams. The designer of the decision support system can then match the results of the analysis to the guidelines of the theoretical framework and proceed accordingly.

Suggested Citation

  • Jan Riezebos & Jean-Michel Hoc & Nasser Mebarki & Christos Dimopoulos & Wout Wezel & Guillaume Pinot, 2010. "Design of Scheduling Algorithms," Springer Books, in: Jan C. Fransoo & Toni Waefler & John R. Wilson (ed.), Behavioral Operations in Planning and Scheduling, chapter 0, pages 299-321, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-13382-4_12
    DOI: 10.1007/978-3-642-13382-4_12
    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. Käki, Anssi & Kemppainen, Katariina & Liesiö, Juuso, 2019. "What to do when decision-makers deviate from model recommendations? Empirical evidence from hydropower industry," European Journal of Operational Research, Elsevier, vol. 278(3), pages 869-882.
    2. Cardin, Olivier & Mebarki, Nasser & Pinot, Guillaume, 2013. "A study of the robustness of the group scheduling method using an emulation of a complex FMS," International Journal of Production Economics, Elsevier, vol. 146(1), pages 199-207.

    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:sprchp:978-3-642-13382-4_12. 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.