Congratulations to visiting PhD student, Yanling Zhuang, of McMaster University, for being awarded the Smart Freight Symposium Best Student Presentation on November 26, 2021. The award comes with a $1,000 cash prize made possible by the generous sponsorship of Kinaxis Canada.
Yanling Zhuang is a fourth-year PhD candidate student in Management Science at Dalian University of Technology. She visited DeGroote School of Business, McMaster University from Sep. 2019 to Sep. 2021, under the co-supervision of Dr. Yun Zhou, Dr. Yufei Yuan, Dr. Elkafi Hassini of McMaster University, and Dr. Xiangpei Hu of Zhejiang University. Yanling has received several awards and recognitions, including the Outstanding College Student of Dalian University of Technology and the National Scholarship of the Ministry of Education of China.
Her primary research interests are in the fields of e-commerce and logistics management, especially the optimization in robotic mobile fulfillment systems
Specifically, she focuses on the order picking optimization, storage assignment, and robot scheduling problems occurring in mobile robots warehouse fulfillment systems. She has finished several projects, cooperated with Dr. Yun Zhou, Dr. Yufei Yuan, Dr. Elkafi Hassini and Dr. Xiangpei Hu, on these optimization problems, and proposed efficient solution procedures to solve these problems, which can achieve very good performances under real-life cases. In particular, for the order picking optimization problem in mobile robots warehouses, their methods can reduce rack movements to picking stations by up to 62% compared with the current practice (tested using a real-world dataset). Through their works, they have also provided several implications for managerial practices.
Yanling deeply appreciates the Smart Freight Symposium that gave her an opportunity to present her works and granted her the Best Student Paper Presentation Award. This award will further strengthen her determination to make valuable contributions to the freight transportation and logistics areas.
