Transportation optimization in large-scalecongestion networksand emerging automation technologies represents an extremely challenging and interesting application field for the operations research and mathematical programming communities. In this talk, we would like to apply and extend a number of integer programming solution techniques to solve a range of large-scale transportation optimization problems, to name a few, vehicle routing problem, cyclic high-speed train timetabling problem and passenger flow state estimation problem using big-data sources.Alternating Direction Method of Multipliers (ADMM) has been widely applied to non-linear optimization problems, while we need to solve many transportation network optimization instances with a large number of integer decision variables.Three recent approaches will be reported: first, how to use the space-time and space-time-state networks to reformulate models with fewer side constraints; second,how to provide a new formulation to fully utilize the Augmented Lagrangian method quickly linearize the associated quadratic term for subproblems. Finally, we also talk about how the traditional cutting plane, Dantzig–Wolfe decomposition and dynamic programmingcan be embedded in the proposed framework to enhance solutions with betterlower bound and upper bound. Three real world applications will be presented: (1) vehicle routing problem with 100 customersbased on a problem solving competition offered by Jingdong Logistics,(2) cyclic train timetabling problem for the Beijing-Shanghai high-speed railway corridor with23 stations and 30 trains, and (3)passenger flow state estimation problem for the Beijing subway network witha total of 18 rail lines, 343 stations and more than 5 million smart card records. Xuesong Zhou is serving as the invited Chief Scientist of Beijing Municipal Commission of Transport, a tenured professor of transportation systems in the School of Sustainable Engineering and the Built Environment at Arizona State University (ASU). Dr. Zhou is currently an Associate Editor of Transportation Research Part C, an Associate Executive Editor-in-Chief of Urban Rail Transit, an Associate Editor of Networks and Spatial Economics, an Editor of Transportation Research Part B. He was the formal Chair of INFORMS Rail Application Section (2016), and the Co-Chair of the IEEE ITS Society Technical Committee on Traffic and Travel Management, as well as a subcommittee chair of the TRB Committee on Transportation Network Modeling (ADB30). Dr. Zhou's research work focuses on dynamic traffic assignment, traffic estimation and prediction, large-scale routing and rail scheduling. He has published more than 50 papers with an H-index of 30.