应刘志远教授邀请，新加坡管理大学王海老师于2019年7月29日上午10:00在交通学院大楼322会议室举行了一场题为“Muti-Objective Online Ride-Matching”的学术报告。报告由张文波老师主持，童蔚萍老师和相关专业的同学们参加了本次报告会。
目前共享交通正在全球范围内普及，以Uber和滴滴为代表的共享交通企业每天需要处理成千上万的订单，如此庞大的交通需求衍生了一系列的问题，包括行程时间估计、车辆分配、供需双方评分机制等问题，本次报告王海老师针对车辆和订单的匹配问题分稳定和时变两种订单状态介绍了如何用多目标方法对车辆进行分配，并分析了根据优化算法进行的实际测试结果。
王海老师首先介绍了共享交通的发展和目前共享交通系统和系统内在与外在的影响因素，在此基础上提出车辆与订单的多目标匹配问题。考虑接驾时间、司机服务质量、司机收入三种因素的基础上，王老师提出了以目标表现和实际表现之差作为自适应权重的匹配优化算法，并进一步证明了实际表现的收敛性，证明了算法的有效性。在实际测试中，这种自适应匹配方法与传统的权重法、多阶段优化方法和最近提出了“稳定匹配”方法进行了比较，实验结果表明在供大于求和供不应求的两种订单状态下，动态匹配方法都优于另外三种传统方法，且能够迅速收敛。接着王老师根据订单状态时变这一实际情况，介绍了原有算法的改进方法，在模拟数据情况下取得了更好的优化结果。
Dr. Wang received a bachelor degree from Tsinghua University, dual Master’s degree in operations research and transportation from MIT, and Ph.D. from MIT Operations Research Center. He is now an Assistant Professor at Singapore Management University, and will visit and teach at Carnegie Mellon University from this fall. His research has focused on methodologies on operations research, data-driven modeling, computational algorithms, and machine learnings, and relevant applications in urban, transportation, logistics, and healthcare systems. Particularly, he is interested in on-demand service and shared transportation. He has papers published in Transportation Science, American Economic Review Papers & Proceedings, Manufacturing & Service Operations Management, and Transportation Research Part B: Methodological. He is serving as the guest-editor for the Special Issue on Innovative Shared Transportation in Transportation Research Part B, as reviewer for more than 20 academic journals, including MS, TS, M&SOM, POM, etc, and named as Chan Wui & Yunyin Rising Star Fellow in Transportation. During his Ph.D. at MIT, he also served as the co-President of MIT Chinese Students & Scholars Association and Chair of MIT-China Innovation and Entrepreneurship Forum.
