報告主題：The Driver-Aide Problem: Coordinated Logistics for Last-Mile Delivery（司機輔助問題：最後一英裡配送的協調物流）

報告時間：6月13日上午10：00

報告地點：旭日樓306教室

報告人：張銳 副教授

主持人：熊慧 教授

報告人簡介：

張銳是美國科羅拉多大學博爾德分校利茲商學院戰略、創業和運營系的副教授。他是商業分析碩士項目的主任。在此之前，他曾擔任運營博士項目的主任。此外，他還是INFORMS Journal on Computing和Networks的副主編。他的研究興趣是定量方法，尤其是規範性分析方法。他的研究聚焦于收益管理問題、最後一英裡配送和社交網絡上的影響力最大化問題。他的工作發表在Operations Research, Manufacturing & Service Operations Management, INFORMS Journal on Computing, INFORMS Journal on Optimization, Naval Research Logistics, European Journal of Operational Research和Networks,等雜志上。此外，他還獲得了多個最佳論文獎。他的作品集被選為2022年INFORMS Computing Society (ICS)獎的亞軍。

報告簡介：

Last-mile delivery is a critical component of logistics networks, accounting for approximately 30%–35% of costs. We model this problem as an integer program with an exponential number of variables and an exponential number of constraints and propose a branch-cut-and-price approach for solving it. Our computational experiments are based on simulated instances built on real-world data provided by an industrial partner and a data set released by Amazon. The instances based on the Amazon data set show that this novel operation can lead to, on average, a 35.8% reduction in routing time and 22.0% in cost savings. More importantly, our results characterize the conditions under which this novel operation mode can lead to significant savings in terms of both the routing time and cost. Our computational results show that the driver aide with both jumper and helper modes is most effective when there are denser service regions and when the truck’s speed is higher (≥10 miles per hour). Coupled with an economic analysis, we come up with rules of thumb (that have close to 100% accuracy) to predict whether to use the aide and in which mode. Empirically, we find that the service delivery routes with greater than 50% of the time devoted to delivery (as opposed to driving) are the ones that provide the greatest benefit. These routes are characterized by a high density of delivery locations.