1.代表性期刊论文

(1) Yimeng Zhang, Xiangrong Tan, Mi Gan*, Xiaobo Liu, Bilge Atasoy, Operational synchromodal transport planning methodologies: Review and roadmap, Transportation Research Part E: Logistics and Transportation Review,2025,194

(2) Qiujun Qian(博士生), Mi Gan*, Xiaoyuan Yang,Empirical analysis of intelligent charging Decisions: Boosting efficiency for electric trucks, Transportation Research Part D: Transport and Environment, 2025, 139: 104572. 

(3)Peng T(博士生), Gan M*, Yao Z, et al. Nonlinear impacts of urban built environment on freight emissions, Transportation Research Part D: Transport and Environment, 2024, 134: 104358.

(4) Li D(博士生), Gan M*, Qiao Y, et al. A MINP model and hybrid heuristic algorithm for railway cold chain service network design problem: a case study of China[J]. International Journal of Production Research, 2024: 1-22

(5)Peng T(博士生), Gan M* , et al. Railway cold chain freight demand forecasting with graph neural networks: A novel GraphARMA-GRU model[J].Expert Systems with Applications, 2024,255(B): 124693.

(6)  Qiujun Qian(博士生), Mi Gan*, Lifei Wei, Zhu Yao, Yuxin He, Behavior-Driven Planning of Electric Truck Charging Infrastructure for Intercity Operations, IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 1558-0016, 1-17 DOI:10.1109/TITS.2024.3375458

(7) Zhu Yao(博士生)，Mi Gan*, Qiujun Qian, Yu Qiao, Lifei Wei，Variation of truck emissions by trip purposes: cases by real-world trajectory data，Transportation Research Part D： Transport and Environment；2023，122，103887:1-25

(8) Gan Mi, Qian Qianjun, Li Dandan, Ai Yi, Xiaobo Liu*,Capturing the swarm intelligence in truckers: The foundation analysis for future swarm robotics in road freight,Swarm and Evolutionary Computation. 2021,6(2),100845 入选美国ACM未来供应链推荐阅读

(9) Gan, Mi ; Nie, Yu* ; Liu, Xiaobo; Zhu, Daoli, Whereabouts of truckers: An empirical study of predictability, Transportation Research Part C: Emerging Technologies, 2019.7, 104:184~195

(10) Yu Juan(博士生)，Gan Mi *; Ni Shaoquan; Chen Dingjun, Multi-objective models and real case study for dual-channel FAP supply chain network design with fuzzy information, Journal of Intelligent Manufacturing, 2018.02, 29(2):389~403

2. 代表性会议论文和汇报

(1) Meitong An, Zhu Yao, Mi Gan*, Shuai Yang; Si Chen, A Convolutional Long Short-Term Memory Forecasting Model of Road Freight Demand and Related Carbon Emissions Estimation: An Empirical Study of Chengdu-Chongqing, 102nd TRB ANNUAL MEETING, Washington D. C. U. S. A,2023.1.8-2023.1.12

(2) Qian Zheng, Zhu Yao, Mi Gan*, A Deep Learning Method for Site Selection of High-Speed Railway Freight Station, 102nd TRB ANNUAL MEETING, Washington D. C. U. S. A , 2023.1.8-2023.1.12

(3) Mi Gan ; Shuai Yang; Si Chen, Dynamic Game Study of Competition and Cooperation Strategy of Railway Inland Ports and Seaports, 96th TRB ANNUAL MEETING, ,2017.1.6-2017.1.8, 

(4) Mi Gan ; Si Chen; Siyu Tao, Regional logistics network design with consider of roadway traffic congestion and service decay, Informs ANNUAL MEETING 2017, 2017.10.22-2017.10.25

(5) Mi Gan, An Eco facility location problem with consider of urban logistics network GHG emissions, China-UK workshop on GHG emissions of urban distribution problem, Newcastle University，United Kingdom，1-5 November 2016 

(6) 甘蜜，考虑货车碳排放的生态物流设施选址问题，2016年京津冀空间优化、交通发展与大气环境改善国际研讨会，中国，石家庄，2016年8月25-26日

(7) Qinglan Huang, Mi Gan*, Ronghui Xie, Analysis On The Competition Between a pair of seaports Under Carbon Emission Constraints, 2020 TRB Annual Meeting. Washington D. C. U. S. A

(8) Xiaobo Liu; Mi Gan* ; Yu Nie, Understanding truck related greenhouse gas emission in urban logistics network, 95th TRB Annual Meeting, , 2016.01.06-2016.01.08