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Dynamic personnel rescheduling : insights and recovery strategies

Broos Maenhout (UGent) and Mario Vanhoucke (UGent)
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Abstract
Personnel rescheduling problems have typically been studied from a static perspective, assuming a single rescheduling decision to be taken for which all disruption information is known. However, companies operate in a dynamic environment and new disruptions arise at different moments in time during the course of the execution of the schedule. In response, the personnel planner resides to (multiple) rerostering and/or allocation decisions to reinstate the workability of the schedule. In this paper, we investigate the dynamic personnel shift and task rescheduling problem and propose different recovery strategies to efficiently restore the personnel schedule. To that purpose, we simulate the operational variability based on input probability distributions for different sources of uncertainty and conduct timely recourse actions whenever indicated by the studied recovery strategies. Insights are provided into the recourse actions with respect to the number and timing of rescheduling decisions, the type of rescheduling decision and the rescheduling time horizon. We assess the trade-off between the rescheduling quality and effort, mapping the efficient recovery strategies using a Pareto front. Based upon these insights, we devise well-performing rules-of-thumb, defining efficient recovery decision strategies that lead to reconstructed personnel schedules of high quality. In addition, we investigate the impact of the timeline uncertainty on the outcome of the recovery strategies.
Keywords
Artificial Intelligence, Management Science and Operations Research, General Engineering, Software, Personnel scheduling, Dynamic rescheduling, Recovery policies, POLICIES, MODELS, NURSES

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Citation

Please use this url to cite or link to this publication:

MLA
Maenhout, Broos, and Mario Vanhoucke. “Dynamic Personnel Rescheduling : Insights and Recovery Strategies.” JOURNAL OF SCHEDULING, 2024, doi:10.1007/s10951-023-00785-7.
APA
Maenhout, B., & Vanhoucke, M. (2024). Dynamic personnel rescheduling : insights and recovery strategies. JOURNAL OF SCHEDULING. https://doi.org/10.1007/s10951-023-00785-7
Chicago author-date
Maenhout, Broos, and Mario Vanhoucke. 2024. “Dynamic Personnel Rescheduling : Insights and Recovery Strategies.” JOURNAL OF SCHEDULING. https://doi.org/10.1007/s10951-023-00785-7.
Chicago author-date (all authors)
Maenhout, Broos, and Mario Vanhoucke. 2024. “Dynamic Personnel Rescheduling : Insights and Recovery Strategies.” JOURNAL OF SCHEDULING. doi:10.1007/s10951-023-00785-7.
Vancouver
1.
Maenhout B, Vanhoucke M. Dynamic personnel rescheduling : insights and recovery strategies. JOURNAL OF SCHEDULING. 2024;
IEEE
[1]
B. Maenhout and M. Vanhoucke, “Dynamic personnel rescheduling : insights and recovery strategies,” JOURNAL OF SCHEDULING, 2024.
@article{01GZ8AVWG7J6QE83DBYMWZPRFA,
  abstract     = {{Personnel rescheduling problems have typically been studied from a static perspective, assuming a single rescheduling decision to be taken for which all disruption information is known. However, companies operate in a dynamic environment and new disruptions arise at different moments in time during the course of the execution of the schedule. In response, the personnel planner resides to (multiple) rerostering and/or allocation decisions to reinstate the workability of the schedule. In this paper, we investigate the dynamic personnel shift and task rescheduling problem and propose different recovery strategies to efficiently restore the personnel schedule. To that purpose, we simulate the operational variability based on input probability distributions for different sources of uncertainty and conduct timely recourse actions whenever indicated by the studied recovery strategies. Insights are provided into the recourse actions with respect to the number and timing of rescheduling decisions, the type of rescheduling decision and the rescheduling time horizon. We assess the trade-off between the rescheduling quality and effort, mapping the efficient recovery strategies using a Pareto front. Based upon these insights, we devise well-performing rules-of-thumb, defining efficient recovery decision strategies that lead to reconstructed personnel schedules of high quality. In addition, we investigate the impact of the timeline uncertainty on the outcome of the recovery strategies.}},
  author       = {{Maenhout, Broos and Vanhoucke, Mario}},
  issn         = {{1094-6136}},
  journal      = {{JOURNAL OF SCHEDULING}},
  keywords     = {{Artificial Intelligence,Management Science and Operations Research,General Engineering,Software,Personnel scheduling,Dynamic rescheduling,Recovery policies,POLICIES,MODELS,NURSES}},
  language     = {{eng}},
  title        = {{Dynamic personnel rescheduling : insights and recovery strategies}},
  url          = {{http://doi.org/10.1007/s10951-023-00785-7}},
  year         = {{2024}},
}

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