Les affordances sont des possibilités d’action offertes par l’environnement : objets, artefacts, technologies. Ce concept a été créé pour compléter la vision fonctionnelle en mettant l’accent sur les actions des utilisateurs et en aidant à identifier les défaillances potentielles ou les effets négatifs que les autres approches ont du mal à identifier. Même si cette approche ne fournira jamais au créateur toutes les actions potentielles de l’utilisateur, elle permet de changer de point de vue pour en adopter un plus réfléchi et de concevoir des modèles organisationnels et des technologies plus sûrs et plus faciles à utiliser.

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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