Le bien-être au travail est une question d’équilibre : entre les ressources et les facteurs de stress au travail; entre les ressources personnelles et les vulnérabilités; entre les ressources financières et les demandes; entre les ressources sociales et les facteurs de stress; et enfin, entre les conditions de travail positives et négatives. Derrière ces continuums est une préoccupation des travailleurs de se sentir bien et la préoccupation des organisations pour améliorer la productivité des travailleurs.

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Robotic warehouses have transformed logistics, prioritizing speed and efficiency. However, traditional static priority systems often leave low-priority customers facing excessive delays, raising concerns about fairness. This research, based on Invia, a robotic warehouse company, proposes a dynamic priority allocation model to balance efficiency and fairness. By adjusting order priorities over time, this approach ensures that both high-priority and long-waiting low-priority orders receive timely fulfillment. Through stochastic modeling and simulations, we demonstrate that dynamic prioritization reduces delays compared to static and first-come, first-served (FCFS) models. Case studies in e-commerce and healthcare logistics illustrate the broader impact of fairness in automation. As industries increasingly rely on AI-driven decision-making, the balance between efficiency and equity becomes critical. This research challenges the assumption that robotic warehouses should optimize for speed alone and advocates for a future where fairness plays a central role in automated commerce.
YUAN Zhe - EMLV |
- Recherche
- Logistique et Supply Chain, Transformation Digitale