On the partitioning of dynamic workforce scheduling problems

Y. Borenstein, Nazaraf Shah, E. Tsang, R. Dorne, A. Alsheddy, C. Voudouris

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    This problem is based on the British Telecom workforce scheduling problem, in which technicians (with different skills) are assigned to tasks (which require different skills) which arrive (partially) dynamically during the day. In order to manage their workforce, British Telecom divides the different regions into several areas. At the beginning of each day all the technicians in a region are assigned to one of these areas. During the day, each technician is limited to tasks within the assigned area.

    This effectively decomposes a large dynamic scheduling problem into smaller problems. On one hand, it makes the problem more manageable. On the other hand, it gives rise to, potentially, a mismatch between technicians and tasks within an area. Furthermore, it prevents technicians from being assigned a job which is just outside their area but happens to be close to where they are currently working.

    This paper studies the effect of the number of partitions on the expected objective (number of completed tasks) that a rule-based system (responsible for the dynamic assignment and reassignment of tasks to resources following dynamic events) can reach.
    Original languageEnglish
    Pages (from-to)411-425
    JournalJournal of Scheduling
    Volume13
    Issue number4
    DOIs
    Publication statusPublished - 2010

    Bibliographical note

    The full text of this item is not available from the repository.
    The final publication is available at www.springerlink.com

    Keywords

    • dynamic workforce scheduling
    • dynamic vehicle routing
    • partitioning
    • decomposition
    • stochastic model

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  • Cite this

    Borenstein, Y., Shah, N., Tsang, E., Dorne, R., Alsheddy, A., & Voudouris, C. (2010). On the partitioning of dynamic workforce scheduling problems. Journal of Scheduling, 13(4), 411-425. https://doi.org/10.1007/s10951-009-0152-6