Machine Learning-Assisted Design of Electrode Microstructures and Flow Fields for Redox Flow Batteries by Dr.Shuaibin Wan
Speaker: Dr.Yandong He
Topic: An effective metaheuristic for the last mile delivery with roaming delivery locations and stochastic travel times by Dr.Yandong He
Time & Date: on March 16 (Thursday) 09:00-10:00 (Beijing Time)
Zoom Meeting:
https://cuhk
Zoom Meeting ID: 914 2537 9503
Password：123456
Abstract:
We consider the last mile delivery system with roaming delivery locations and stochastic travel times. The problem is formulated as a two-stage stochastic programming model with recourses, its objective is to minimize the total travel time of serving a set of customers with roaming delivery locations under stochastic travel times. We propose an effective metaheuristic integrating a sampling strategy (sample average approximation, SAA) to solve stochastic model, our metaheuristic consists of random selection-greedy insertion (RSGI) and hybrid iterated greedy algorithm with route re-optimization and simulated annealing (HIGRR-SA). The computational study shows that our solution method has an advantage in terms of solution quality and computational time. The comparison of the stochastic and deterministic solutions shows that a significant reduction in expected travel time can be achieved as well as a smaller fluctuation considering stochastic information.
Biography:
Yandong He received the B.Sc. degree in industrial engineering from the Hubei University of Automotive Technology, China, in 2012, and the M.Sc. in industrial engineering and Ph.D. degrees in management science and engineering from Chongqing University, China, in 2015 and 2018, respectively. In 2017, as a joint PhD. student, he was supervised by Professor Tom van Woensel in the Technology University of Eindhoven, Netherlands for a year on the last mile delivery. After that, He worked as a postdoctoral researcher in the Department of Industrial Engineering, Graduate School at Shenzhen, Tsinghua University. His research interests include operations research, routing and scheduling.
