主题:  Optimizing Spatial Service Systems: New Practice and Data-Driven Guidelines

空间服务系统的优化：新实践模式与数据驱动型管理指南

时间: 2026年5月28日 晚上20：00

地点: 腾讯会议 520-928-855

主讲人: Sheng Liu 教授

Bio: Sheng Liu is an Assistant Professor of Operations Management and Statistics at the Rotman School of Management, University of Toronto. Sheng's research focuses on solving operations problems in supply chains, transportation, and logistics systems through optimization and data analytics. His industry experience includes consulting or working for organizations such as JD.com, Sport Chek, Ninja Van, Hungerhub, Amazon, and Lyft. Sheng also strives to improve decision outcomes for vulnerable groups, motivated by collaboration with nonprofit organizations, including charities and food banks. His work has been recognized with several awards and paper competitions, including the INFORMS PSOR Best Paper Award, INFORMS TSL Outstanding Paper Award, and the M&SOM Data-Driven Research Competition. He currently serves as an associate editor of Transportation Science, a senior editor of Production and Operations Management, and an Editorial Review Board member of Service Science.

Abstract: Large-scale spatial service systems, including mobility and logistics, require scalable and interpretable policies to match supply and demand. In the first part of the talk, I will discuss how new tactical zoning methods can enhance real-world logistics operations, which leads to a field implementation in Southeast Asia. In the second part, I will present a new data-driven, machine learning augmented solution framework for solving network optimization problems with endogenous choice models. This is demonstrated in the case of electrifying bike-share systems at scale.