School of Transportation, Beijing Jiaotong University
September 12, 2023, 11:00, Room GC G1 515 (click here for the map)
Current metropolitan public transportation systems employ fixed-capacity vehicles; however, this makes it challenging to match uneven passenger demand over time and space. Fortunately, emerging modular vehicle technology makes it practical for vehicles to dynamically adjust their capabilities during operation, which holds the promise of being one of the solutions to the above problem. This technology introduces the concept of dynamic capacity, which refers to the number of modular units comprising an MV can be potentially changed at different times and stops. For the purpose of better applying the features of modularized buses and reducing the operating costs without compromising the quality of service, we have done the following researches: (1) we develop a data-driven distributionally robust optimization model at the line operation level that considers time-varying capacity over all possible demand distributions within the ambiguity set. (2) Further, we formalize and analyze the integrated problem of timetables, vehicle schedules, and dynamic allocations of capacity with MVs in a network under uncertainty. To efficiently solve the above models, we first design customized benders decomposition algorithms and then incorporate them into a rolling horizon optimization framework to solve large-scale problems. Finally, we conduct a series of real-world case studies based on the operational data of the Beijing Public Transportation Corporation and validate the effectiveness of the proposed approaches.
Dongyang Xia is a PhD candidate at School of Transportation at Beijing Jiaotong University. He is currently enrolled as a visiting PhD student at Delft University of Technology under the supervision of Dr. Shadi Sharif Azadeh. His research focuses on the optimization of public transport operations under uncertainty. Dongyang's research aims to improve the operational efficiency and service quality of urban public transport. His PhD project was carried out in collaboration with an industry partner the Beijing Public Transportation Corporation, where he applies operations research optimization techniques to support their decision-making. As of 2024, he will start a postdoc position in the SUM lab for SINERGI project (ERANET funded).