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講座:Data-Driven Approaches in Smart City Operations

來源:上海交通大學安泰經濟與管理學院 | 2019-11-15 | 發布:經管之家

題目:Data-Driven Approaches in Smart City Operations

嘉賓:劉晟 助理教授多倫多大學

主持人:宋穎達 助理教授上海交通大學安泰經濟與管理學院

時間:2019年12月06日(周五) 10:00-11:30

地點:上海交通大學徐匯校區包圖 A303

內容簡介:

Smart city operations have received growing attention from the operations management community. This talk presents two projects that build data-driven solutions for city operations planning and management. The first part is devoted to the emerging food delivery operations. Working with a major food delivery service provider in China, we develop a data-driven optimization framework to minimize the expected delivery delay. Motivated by the real-world data set, we propose a machine learning approach to predict the actual travel time considering drivers' behaviors. Combined with the travel time prediction, our optimization framework is flexible and yields significantly better results than existing models that assume drivers follow the shortest routes. In the second part, we showcase how the real-world bike trajectory data can help improve the bike lane planning decision for city managers. We integrate the two objectives, coverage and continuity, into the bike lane planning model in view of the cyclists' utility functions. Efficient reformulations and algorithms are presented to solve the large-scale planning problem.

演講人簡介:

Sheng Liu is an Assistant Professor of Operations Management and Statistics at the Rotman School of Management. His research interests lie in smart city operations, data analytics, and optimization. His research has been published in Operations Research, Manufacturing & Service Operations Management, and INFORMS Journal on Computing. He holds a PhD in Operations Research from the Department of Industrial Engineering & Operations Research at the University of California, Berkeley. He has industry experience in Lyft and Amazon (as a Data/Research Scientist intern).

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