题目: 共享出行供需匹配系统的优化 Optimization for on-demand matching process in ride-sourcing systems

演讲人: 柯锦涛，香港理工大学

时间: 2021年7月7日下午 13:00-14:30

地点: 腾讯会议ID: 622452958, 密码：277998

讲座摘要:

As a symbolic icon for smart mobility in recent years, ride-sourcing service, provided by digital platforms like DiDi, Uber and Lyft, has been playing an increasingly important role in meeting mobility needs by efficiently connecting passengers and dedicated drivers through online platforms. Despite its great success in business, ride-sourcing service has also aroused many challenging issues in operations, management, and regulations, from the perspective of different stakeholders, including both private sectors (ride-sourcing platforms) and public sectors (governments). One critical issue in platform operations for ride-sourcing service is the optimizations for on-demand matching process between idle drivers (supply) and waiting passengers (demand). In particular, this talk will present a novel model to jointly optimize two key decision variables in on-demand ride matching process－matching time interval and matching radius－under different supply and demand levels. The model will enable ride-sourcing platforms to dynamically adjust their matching time interval and matching radius in response to changing supply and demand in a dynamic system. Additionally, this talk will discuss how to integrate advances of reinforcement learning approaches into traditional optimization models to further improve the efficiency of the driver-passenger matching procedure. It is shown that pure optimization models are generally myopic and only focus on immediate feedbacks during the current time interval without considering future system rewards. In contrast, the combination of reinforcement learning and optimization can be more far-sighted by considering the interactions between platform operations and system dynamics, and thus achieve better performance over a long horizon.

演讲嘉宾简介:

柯锦涛，博士，香港理工大学研究助理教授。分别于浙江大学和香港科技大学获得学士和博士学位。致力于共享出行系统运营与监管、大数据驱动的城市多模式交通系统的管理与优化、基于机器学习的短时交通需求量预测、交通定价与博弈等方面的研究。在Transportation Research Part A/B/C/E, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Intelligence Transportation System等期刊发表SCI/SSCI期刊论文20篇，论文总引用数超过1000次。现担任国际期刊Transportation Research Part C青年编委。