管理科学与工程系学术讲座

题目:On-Time Last Mile Delivery: Order Assignment with Travel Time Predictors

更准点的最后一公里配送：基于行程预测的派单方法

演讲人:何龙，新加坡国立大学
时间:2020年6月12日上午10:30
参与方式:zoom云视频会议；

会议号: 94450727832会议密码: 299363

讲座摘要:

We study how delivery data can be applied to improve the on-time performance of last mile delivery services. Motivated by the delivery operations and data of a food delivery service provider, we discuss a framework that integrates the travel time predictors with the order assignment optimization. Such integration enables us to capture the driver’s routing behavior in practice, where the driver’s decision-making process is often unobservable or intricate to model. Focusing on the order assignment problem as an example, we discuss the classes of tractable predictors and prediction models that are highly compatible with the existing stochastic and robust optimization tools. We further provide reformulations of the integrated models, which can be efficiently solved with the proposed branch-and-price algorithm. Moreover, we propose two simple heuristics for the multiperiod order assignment problem, which are built upon the single-period solutions. Using the delivery data, our numerical experiments on a real-world application not only demonstrate the superior performance of our proposed order assignment models with travel time predictors, but also highlight the importance of learning the behavioral aspects from the operational data. We find that large sample size does not necessarily compensate for the misspecification of the driver’s routing behavior

演讲嘉宾简介:

Long He is an assistant professor in Department of Analytics & Operations (DAO) at NUS Business School, National University of Singapore. He received his Ph.D. in Operations Research from the University of California, Berkeley, and his B.Eng. in Logistics Management and Engineering from HKUST. His current research involves using data-related approaches to address problems in smart city operations (e.g., vehicle sharing, last-mile delivery) and supply chain management. He has received MSOM best paper award and INFORMS TSL best paper award.