New retail concepts that embrace a hybrid “online + offline” business paradigm promise super-fast order fulfillment of groceries within the next hour. In this ”online + offline” retail scenario, it is crucial to efficiently fulfill many online orders within the stipulated time while adhering to the layout rules of offline retail products. Zone-picking and overhead conveyors have been introduced to cope with the significant volume of orders batching, picking, and delivering fresh products. This has led to a new integrated order batching and picking decision problem, aiming for human-machine reconciliation in Industry 5.0. For such a problem, two new mixed integer linear programming models are developed, considering minimizing the number of picking task releases and the total delay time of all orders. The computational complexity of the two problems is provided. A customized two-stage heuristic framework is developed to solve the two models with distinct solution space structures. Numerical experiments have been conducted to test the performance of the proposed methods and provide solution analysis for practical insights. The results show that the proposed heuristic reduces the number of picking tasks for workers by 19% and the total delay in completing orders by 74% compared to prevailing store practices. The proposed framework complements the existing models in the literature. It contributes to developing a comprehensive analysis of order picking by integrating human factors into operational efficiency improvement in the new retailing industry.
Zhang, X., Guo, P., Xin, J., D'Ariano, A., Wang, Y. (2025). Enabling within-the-hour fresh food deliveries: Integrated order batching and zone-picking through overhead conveyors. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 199 [10.1016/j.tre.2025.104133].
Enabling within-the-hour fresh food deliveries: Integrated order batching and zone-picking through overhead conveyors
D'Ariano A.;
2025-01-01
Abstract
New retail concepts that embrace a hybrid “online + offline” business paradigm promise super-fast order fulfillment of groceries within the next hour. In this ”online + offline” retail scenario, it is crucial to efficiently fulfill many online orders within the stipulated time while adhering to the layout rules of offline retail products. Zone-picking and overhead conveyors have been introduced to cope with the significant volume of orders batching, picking, and delivering fresh products. This has led to a new integrated order batching and picking decision problem, aiming for human-machine reconciliation in Industry 5.0. For such a problem, two new mixed integer linear programming models are developed, considering minimizing the number of picking task releases and the total delay time of all orders. The computational complexity of the two problems is provided. A customized two-stage heuristic framework is developed to solve the two models with distinct solution space structures. Numerical experiments have been conducted to test the performance of the proposed methods and provide solution analysis for practical insights. The results show that the proposed heuristic reduces the number of picking tasks for workers by 19% and the total delay in completing orders by 74% compared to prevailing store practices. The proposed framework complements the existing models in the literature. It contributes to developing a comprehensive analysis of order picking by integrating human factors into operational efficiency improvement in the new retailing industry.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
