A Bi-objective shift scheduling problem considering circadian cycle disruptions, fatigue and imbalance workers

Karen Niño-Mora et al.

Annals of Operations Research2026https://doi.org/10.1007/s10479-026-07112-1article
AJG 3ABDC A
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0.50

Abstract

In today’s fast-paced world, driven by technological developments, workers face increasing workloads, leading to fatigue, stress, and disruptions in their circadian cycles. These biological, physical, and behavioral effects negatively impact worker health, safety, and productivity. To address this challenge, this study proposes an optimization of workforce scheduling considering fatigue management and productivity balance through a Mixed Integer Programming (MIP) approach. Two objective functions are considered: The first objective focuses on fatigue control by implementing a rest-rotation system. To enforce compliance, two additional penalties are introduced: (1) a preference based penalty for workers assigned to preferred shifts outside their planned rotation, and (2) an out of rotation penalty for assignments that violate both rotation schedules and worker preferences. The second objective aims to maximize productivity by minimizing the workload imbalance among workers. The model was tested in 40 small and medium instances, demonstrating its ability to optimize the distribution of the workforce while balancing fatigue management and productivity. The results show that integrating wellness considerations into personnel scheduling improves productivity while reducing worker fatigue, as shifts align with natural rest and fatigue. Likewise, results provide valuable information for decision makers in workforce planning, allowing them to adjust scheduling strategies based on operational priorities as well as the health of workers is highly considered.

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https://doi.org/https://doi.org/10.1007/s10479-026-07112-1

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@article{karen2026,
  title        = {{A Bi-objective shift scheduling problem considering circadian cycle disruptions, fatigue and imbalance workers}},
  author       = {Karen Niño-Mora et al.},
  journal      = {Annals of Operations Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10479-026-07112-1},
}

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F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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R · text relevance †0.50 × 0.4 = 0.20

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