Profile

DENG Lianbo

Professor | Ph.D. Supervisor | Director, Rail Transit Operations Research Institute

Overview

DENG Lianbo, male, born in May 1977 in Changtu County, Tieling City, Liaoning Province. He holds a Ph.D. and is currently a Full Professor and Ph.D. supervisor at Central South University, where he also serves as Director of the Rail Transit Operations Research Institute.

He received his B.Eng. in Transportation Engineering from Central South University (School of Economics and Management) in 2000, after which he joined Guangzhou Railway Group Corporation. He obtained his Ph.D. in Transportation Engineering from Central South University in 2007, was promoted to Associate Professor in 2008, and conducted research as a visiting scholar at Newcastle University, UK (Oct. 2011 – Oct. 2012).

Research Interests

•  Theory and Methods for High-Speed Railway Transportation Organization Optimization

•  Urban Rail Transit Operations Management Theory and Applications

•  Public Transit Network Optimization Theory

•  Transportation Operations Management and Information Systems

Professional Affiliations

•  Council Member, Chinese Society of Management Science and Engineering (2017–)

•  Council Member, Higher Education Management Branch, Chinese Society of Optimal, Overall Planning and Economic Mathematics (2018–)

•  Chair, Technical Committee on Railway Passenger Service Organization, World Transport Convention (WTC) (2017–)

•  Committee Member, Transportation Systems Engineering Professional Committee, Systems Engineering Society of China (2023–, 10th term)

•  Executive Editorial Board Member, Journal of Transportation Systems Engineering and Information Technology (2021–)

•  Editorial Board Member, Journal of the China Railway Society (2025–)

•  Peer Reviewer for leading domestic and international journals including Journal of the China Railway Society, Railway Sciences and Engineering, Journal of Southwest Jiaotong University, Journal of Tongji University, Journal of Wuhan University of Technology, Transportation Research, Transport Policy, etc.

•  Peer Reviewer for national science and technology programs including the National Natural Science Foundation of China (NSFC)

Education

•  B.Eng. in Transportation Engineering, School of Economics and Management, Central South University, 2000

•  Ph.D. in Transportation Engineering, School of Traffic and Transportation Engineering, Central South University, 2007

•  Visiting Scholar, Newcastle University, UK, Oct. 2011 – Oct. 2012

Teaching

•  Railway Train Operations (Undergraduate, 2013–)

◦  Transportation Organization (Master’s level, 2013–2015)

•  High-Speed Railway Transportation Organization Series (Undergraduate, 2008–)

◦  Introduction to High-Speed Railway (2008–2011)

◦  Modern Railway Technologies and Equipment (2012–2014)

◦  High-Speed Railway Operations Management (2015–)

•  Theory and Methods for Rail Transit Operations (Master’s & Ph.D., 2015–)

◦  Modern Optimization Theory and Methods (Ph.D., 2015)

◦  Transportation Systems Optimization and Simulation (Master’s / Ph.D., 2016–)

•  Software Technology Series (Undergraduate, 2008–2010)

◦  Fundamentals of Computer Software Technology (2008–2010); Database Technology (2010); C Programming

•  Rail Transit Operations Technology Progress and Academic Frontier Lectures (Undergraduate / Master’s / Ph.D., 2012–)

Graduate Enrollment Disciplines

•  0823 Transportation Engineering (Academic Degree) – Transportation Planning and Management

•  0861 Transportation Engineering (Professional Degree)

•  140500 Intelligent Science and Technology

Research Projects (Selected)

[22]  Sub-project of National Key R&D Program (2023YFB2304103-04): Passenger Train Service Plan Compilation Technology for Multi-Scenario Collaboration, 2023–2026.

[21]  Hunan Provincial Natural Science Foundation General Project (2023JJ30703): Multi-Strategy Collaborative Optimization Method for High-Speed Rail Ticket Revenue Management, 2023–2025.

[20]  Hunan Intercity Railway Co., Ltd.: Operations Management Consulting Service (Passenger Flow Analysis, Station Surveys, Operations Improvement), Jun.–Aug. 2023.

[19]  Guangzhou Metro Design and Research Institute Co., Ltd.: Key Technologies for Bus-Oriented Transformation of Existing Intercity Railways and Multi-Network Integration, Jan.–Dec. 2023.

[18]  National Natural Science Foundation of China – High-Speed Railway Joint Fund Key Project (U1834209): Theory and Methods for Intelligent High-Speed Railway Dispatching Based on Collaborative Command, Jan. 2019–Dec. 2022. (PI)

[17]  China Railway Siyuan Survey and Design Group (2017K015-1): Research on Evaluation Index System for Hub Capacity Utilization, Dec. 2017–Dec. 2018.

[16]  Guangzhou Metro Group Co., Ltd. (HT170235): Special Research on Network Train Diagram Simulation and Verification System Development, Jan. 2017–Dec. 2019. (PI)

[15]  National Natural Science Foundation of China General Project (71471179): Optimization of Urban Rail Ticket Fares and Operational Subsidies Based on Train Service Plans, Jan. 2015–Dec. 2018. (PI)

[14]  China Railway Corporation Major Project (2013X004-A-1): Integrated Capacity Utilization of High-Speed and Conventional Rail on Major North-South Corridors, Jun. 2013–Jun. 2015. (Participating Unit PI)

[13]  China Railway Corporation Major Project (2013X004-A-2): Optimization of Traffic Routing and Transportation Organization on Major North-South Corridors, Jun. 2013–Jun. 2015. (Participating Unit PI)

[12]  Fok Ying Tung Education Foundation 13th Young Teachers Research Fund (132017): Coordinated Optimization Theory and Methods for Urban Rail Network Train Diagrams, 2012–2014. (PI, USD 20,000)

[11]  National Natural Science Foundation of China Youth Fund: Optimization Methods for Passenger Network Train Service Plans Based on Elastic Demand, 2010–2012. (PI)

[10]  Ministry of Education Doctoral Program Special Fund: Integrated Optimization of Urban Rail Train Service Plans and Pricing Strategies, 2010–2012. (PI)

[9]  Hunan Provincial Natural Science Foundation: Urban Rail Train Service Plans and Pricing Strategy Research, 2010–2012. (PI)

[8]  Open Fund of State Key Laboratory of Rail Traffic Control and Safety: Optimization Models and Methods for Passenger Dedicated Line Train Service Plans, Jan. 2007–Jun. 2008. (PI)

[7]  National Science and Technology Support Program (2011BAG01B01): Key Technologies and System Development for Urban Rail Transportation Organization in a Network Environment, Sep. 2011–Dec. 2013. (Rank 2)

[6]  National Natural Science Foundation of China (70771116): Theory and Methods for Rail Transit Passenger Train Organization, 2008–2010. (Rank 2)

[5]  Ministry of Education Doctoral Program Special Fund (20060533036): Analysis of Railway Passenger Travel Behavior and Passenger Flow Assignment, 2007–2009. (Rank 2)

[4]  National Natural Science Foundation of China (70471047): Research on Optimization and Evaluation of Passenger Train Service Plans, 2005–2007. (Rank 6)

[3]  China Railway Siyuan Survey and Design Institute: Research on Passenger Train Service Plans for Wuhan-Guangzhou and Zhengzhou-Xi’an High-Speed Lines, 2004. (Rank 3)

[2]  China Railway Siyuan Survey and Design Institute: Optimization of Passenger Dedicated Line Train Service Plans and Software Development, 2004–2006. (Rank 2)

[1]  Changsha Science and Technology Bureau: Research on Countermeasures to Improve Road Traffic Conditions in Changsha, 2006. (Participant)

Selected Publications (Recent)

[1]  Energy consumption analysis of urban rail fast and slow train modes based on train running curve optimization. Energy Reports, 2024(11): 412–422.

[2]  Joint Optimization of Multistage Pricing and Seat Allocation for High-Speed Railways Integrating Pre-Sale Period Division. IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2023.3324814.

[3]  DENG Lianbo, CHEN Chen, JING Enwei, ZHANG Ying, HUO Liang. Optimization of High-Speed Maglev Station Train Operations and Capacity Analysis. Journal of Railway Science and Engineering, 2023, 20(11): 4041–4049.

[4]  Urban Rail Transit Subsidy Optimization Model Based on Travel Distance. Journal of Railway Science and Engineering, DOI: 10.19713/j.cnki.43-1423/u.T20221349.

[5]  Urban Rail Transit Subsidy Optimization Model Based on Travel Cost. Journal of Railway Science and Engineering, DOI: 10.19713/j.cnki.43-1423/u.T20230213.

[6]  Integrated energy-efficient optimization for urban rail transit timetable. IET Intelligent Transport Systems, 10.1049/itr2.12377.

[7]  Multiobjective Collaborative Optimization Method for the Urban Rail Multirouting Train Operation Plan. Journal of Advanced Transportation, vol. 2023, https://doi.org/10.1155/2023/3897353.

[8]  Optimization of Differentiated Fares and Subsidies for Different Urban Rail Transit Users. Computers & Industrial Engineering, 2023, https://doi.org/10.1016/j.cie.2023.109144.

[9]  A line planning approach based on time-varying demand for high-speed rail under the combined operation of periodic and aperiodic services. Computers & Industrial Engineering, 2023(185): 109665.

[10]  Seat allocation optimization for railways considering social distancing during the post-pandemic period. Journal of Transport & Health, Volume 33, 2023, https://doi.org/10.1016/j.jth.2023.101691.

[11]  Collaborative optimization of energy-efficient train schedule and train circulation plan for urban rail. Energy, 263 (2023), 125599: https://doi.org/10.1016/j.energy.2022.125599.

[12]  Train Operation Curve Optimization for an Urban Rail Interval With Multi-Parameter Adjustment. Transportation Research Record, 2022, 2676(12): 811–826.

[13]  Differentiated Fare and Subsidy Optimization for Urban Rail Transit. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(5): 26–36.

[14]  Analysis of High-Speed Railway Overbooking Strategies Based on Stochastic Programming. Journal of Railway Science and Engineering, 2022, 19(10): 2813–2819.

[15]  Multi-level and Multi-metric Hub Capacity Utilization Evaluation with Hierarchical Weighting. Journal of Railway Science and Engineering, 2022, 19(3): 625–633.

[16]  The laws of wagon accumulation cost of the relaxed fixed time accumulation mode. IET Intelligent Transport Systems, 16: 445–458 (2022).

[17]  Vehicle Scheduling Optimization for Railway Field Survey Logistics. Industrial Engineering, 2022, 25(04): 158–164.

[18]  Optimization Problem of Pricing and Seat Allocation Based on Bi-Level Multi-Follower Programming in High-Speed Railway. Journal of Advanced Transportation, vol. 2021, Article ID 5316574, 15 pages, 2021. https://doi.org/10.1155/2021/5316574.

[19]  B-spline Fitting Method for Urban Rail Section Running Time and Optimal Energy Consumption Value Function. Journal of Railway Science and Engineering, 2021, 18(09): 2461–2468.

[20]  Optimization Method for Energy-Saving Train Timetables in Urban Rail Transit. Systems Engineering - Theory & Practice, 2021, 41(6): 1486–1495.

[21]  Urban Rail Train Section Operation Strategy Optimization Based on Multi-speed Regulation. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(2): 111–118.

[22]  Fitting Method of Optimal Energy-Running Time Curve Based on Train Operation Data of an Urban Rail Section. Journal of Advanced Transportation, vol. 2021, Article ID 6663022, 14 pages, 2021. https://doi.org/10.1155/2021/6663022.

[23]  Profit Maximization Model with Fare Structures and Subsidy Constraints for Urban Rail Transit. Journal of Advanced Transportation, vol. 2021, Article ID 6659384, 14 pages, 2021. https://doi.org/10.1155/2021/6659384.

[24]  Hub Capacity Utilization Evaluation Method Based on Subsystem Division. Railway Computer Application, 2021, 30(1): 10–14.

[25]  Zone Fare System Design in a Rail Transit Line. Journal of Advanced Transportation, vol. 2020, Article ID 2470579, 10 pages, 2020. https://doi.org/10.1155/2020/2470579.

[26]  Optimization Method of Operational Subsidy Minimization in Urban Rail Transit. Computers & Industrial Engineering, 2020, vol. 149, 106739. https://doi.org/10.1016/j.cie.2020.106739.

[27]  A two-dimensional clustering method for high-speed railway trains in China based on train characteristics and operational performance. IEEE Access, 2020, vol. 8: 81918–81931. DOI: 10.1109/ACCESS.2020.2991638.

[28]  Optimizing a High-speed Railway Operation Plan based on the Train Capacity and Service Frequency. Journal of Transportation Engineering, Part A: Systems, 2020, 146(10): 04020109.

[29]  Optimal design of feeder-bus network with split delivery. Journal of Transportation Engineering, Part A: Systems, 2020, 146(3): 04019078, 1–15.

[30]  Simultaneous line planning and timetabling based on a combinational travel network for both trains and passengers: a mixed-integer linear programming approach. Transportmetrica A: Transport Science, 2020, 16(4): 1–39.

[31]  Optimization of Urban Rail Transit-Related Bus Feeder Network with Split Delivery Demand. Journal of Shenzhen University, 2020, 37(2): 121–129.

[32]  Theoretical Analysis of Urban Rail Transit System Regulation and Operational Subsidies. Science & Technology Progress and Policy, 2019, 36(S6): 25–31.

[33]  Divide-and-Conquer Dynamic Pricing Optimization for High-Speed Railways Based on Seat Quota Allocation. Journal of Railway Science and Engineering, 2019, 16(10): 2407–2413.

[34]  Passenger Flow Pushing Assignment Method for an Urban Rail Network Based on Hierarchical Path and Line Decomposition. Sustainability, 2019, 11(22): 6441.

[35]  Optimization of Flat-Fare Differentiated Pricing Strategies for Urban Bus Networks. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(05): 128–134.

[36]  Transfer Coordination for Urban Rail Network Train Plans Based on Dynamic Optimization. Railway Computer Application, 2019, 28(07): 66–70.

[37]  Integrated Optimization Method of Operational Subsidy with Fare for Urban Rail Transit. Computers & Industrial Engineering, 127 (2019): 1153–1163.

[38]  Optimization of Intercity Railway Train Timetables Based on Multi-Tempo Combinations. Journal of Southwest Jiaotong University, 2019, 54(04): 831–839.

[39]  Optimal Design for Long-Distance Cross-Line Passenger Transportation Plans. Journal of the China Railway Society, 2018, 40(7): 17–24.

[40]  External Benefits and Subsidy Analysis of Urban Rail Transit. Railway Procurement and Logistics, 2018, (5): 23–25.

[41]  Optimization of Operational Subsidy Amount for Urban Rail Transit. Journal of Railway Science and Engineering, 2018, 15(01): 226–232.

[42]  Optimization of High-Speed Railway Network Train Diagrams Based on Sequencing Optimization. Journal of Railway Science and Engineering, 2018, 15(03): 551–558.

[43]  Multi-periodic train timetabling using a period-type-based Lagrangian relaxation decomposition. Transportation Research Part B, 2017, 105: 144–173.

[44]  Subway Zone Fare Optimization Based on Minimum Fare Rate Deviation. Journal of Railway Science and Engineering, 2017, 14(11): 2473–2479.

[45]  Coordinated ramp metering with equity consideration using reinforcement learning. ASCE's Journal of Transportation Engineering, Part A: Systems, 2017, 143(7): 04017028.

[46]  Optimization of Fare Strategies for Urban Rail Transit Lines. Systems Engineering - Theory & Practice, 2016, 36(6): 1568–1575.

[47]  Correlation Analysis of Passenger Flow and Train Frequency on Beijing-Shanghai and Beijing-Guangzhou High-Speed Railways. Railway Transport and Economy, 2016, 8: 23–29.

[48]  Congestion avoidance routing based on large-scale social signals. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(6): 2613–2626.

[49]  Crew Scheduling Considering both Crew Duty Time Difference and Cost on Urban Rail System. PROMET - Traffic & Transportation, 2016, 28(5): 449–460.

[50]  Fare optimality analysis of urban rail transit under various objective functions. Discrete Dynamics in Nature and Society, Vol. 2014, Article ID 910736, 8 pages, 2014. doi: 10.1155/2014/910736.

[51]  Optimal Coordinated Strategy Analysis for the Procurement Logistics of a Steel Group. Mathematical Problems in Engineering, vol. 2014, Article ID 436512, 7 pages, 2014. doi: 10.1155/2014/436512.

[52]  Coordination optimization of the first and last trains' departure time on urban rail transit network. Advances in Mechanical Engineering, Volume 2013 (2013), Article ID 848292.

[53]  Optimal design of the feeder-bus network based on the transfer system. Discrete Dynamics in Nature and Society, Volume 2013 (2013), Article ID 483682.

[54]  The effect of train formation length and service frequency on the determination of train schedules. Proceedings of the IMechE, Part F: Journal of Rail and Rapid Transit, 2014, 228(4): 378–388.

[55]  Optimization of Direct Train Service Plans for Intercity Railways. Journal of Railway Science and Engineering, 2013, 10(6): 41–46.

[56]  Teaching of Railway Train Operations Course Under the Plan for Excellence Engineers. China Science and Education Innovation, 2013, (20): 148, 150.

[57]  Optimization of Urban Rail Transit-Coordinated Bus Feeder Network Based on Transfer Network. Journal of Railway Science and Engineering, 2012, 9(6): 77–83.

[58]  Research on Urban Rail Train Service Plans Based on Elastic Demand. Journal of the China Railway Society, 2012, 34(12): 16–25.

[59]  Optimization of train timetable for urban rail transit in multi-routes mode. Journal of Modern Transportation, 2011, 19(4): 233–239.

[60]  Dynamic Programming Method for Transportation Network Construction Sequencing. Operations Research and Management Science, 2010, 19(5): 45–51.

[61]  Optimization Methods for Urban Rail Train Service Plans. Chinese Science and Technology Papers Online, 2010, 5(10): 767–772.

[62]  Optimization of Passenger Train Stop Plan. China Railway Science, 2009, 30(4): 102–107.

[63]  Optimization Research on Passenger Train Service Plans for Passenger Dedicated Lines. Ph.D. Dissertation, Central South University, 2007, Changsha, Hunan.

[64]  Bilevel Programming Model and Algorithm for Passenger Train Service Plans. China Railway Science, 2007, 28(3): 110–116.

[65]  Unit Production Cost Analysis for Logistics Enterprises. Mathematics in Practice and Theory, 2007, 37(16): 12–17.

[66]  Algorithm Research for a Class of Personnel Recruitment Problems. Operations Research and Management Science, 2007, 16(4): 149–152.

[67]  Hierarchical Analysis of Railway Passenger Travel Behavior. Journal of Railway Science and Engineering, 2007, 4(3): 79–82.

[68]  Railway Passenger Travel Choice Behavior and Utility Analysis. China Railway Science, 2007, 28(6): 117–121.

[69]  Evaluation Index System for Passenger Train Service Plans. China Railway Science, 2006, 27(3): 106–110.

[70]  System Design of Passenger Train Service Plans for Passenger Dedicated Lines. Systems Engineering, 2006, 24(11): 24–30.

[71]  Multi-generational Competitive Genetic Algorithm for Logistics Vehicle Routing Problems. Journal of Railway Science and Engineering, 2005, 2(5): 75–79.

[72]  Earliest Conflict Optimization Method for Single-Track Train Operation Adjustment. China Railway Science, 2005, 26(1): 106–113.

Awards & Honors

• 2025年， Second Prize, Science and Technology Progress Award, China Railway Society

•2023, BYD Education Fund Outstanding Teacher Award

• 2021, "Design of Autonomous UAV Delivery System Based on Precision Landing Technology and Its APP Architecture," 2nd Prize (Supervisor), 16th National Transportation Science and Technology Competition

• 2017, 7th Qian Xuesen Urban Science Award – Gold Award Nomination in "Urban Traffic Problems"

• 2015, "Dynamic Monitoring and Control Decision System for Large Passenger Flow in Metro," 1st Prize (Supervisor), 10th National Transportation Science and Technology Competition

• 2014, Xinheng Education Fund Outstanding Teacher Award

• 2012, Fok Ying Tung Education Foundation Young Faculty Fund Recipient

Research Group

[1]Name of Research Group:轨道交通营运研究所

Description of Research Group:中南大学在轨道交通营运方面的教学和研究，肇始于1953年长沙铁道学院成立之时的铁道运输系和铁道运输专业。轨道交通营运研究所是在中南大学交通运输工程学院系所调整改革中，于2010年11月组建而成。
研究所依托交通运输工程国家一级重点学科、一级学科博士点和博士后流动站，立足于轨道交通营运管理研究，以高速铁路、城市和城际轨道交通运营组织、运输组织优化和信息系统为主要研究特色。轨道交通营运研究所骨干研究人员包括教授6名，副教授12名，讲师4名，博士和硕士研究生约100名。
研究所的总体发展目标是为我国轨道交通营运管理和决策服务，强化轨道交通营运组织优化理论和关键技术研究，开拓国际化的研究视野，建立一流的轨道交通营运理论研究平台和研究团队。
研究所在轨道交通运营技术方面的研究一直处于国内前列，在旅客运输组织与营销理论、轨道交通运输组织理论、轨道交通流量平衡理论等方面硕果累累。尤其是在网络化铁路客运专线运输组织优化理论与应用、面向市场需求的铁路旅客运输组织和市场营销理论、快捷铁路货物运输组织优化理论与应用、铁路车站作业优化与仿真、铁路售票信息化系统、客票价格和营销策略、列车编组计划及车流组织等方面形成了一批标志性成果，在国内外同具有很高的知名度和影响力。
近年来，立足于轨道交通跨越式发展的国民经济重大需求实际，特别是依托高速铁路、城际和城市轨道交通运输组织需要，对开行方案优化、出行选择行为、换乘网络设计、客流分配理论、运行图编制、客票策略和营销等方面进行了系统研究，并在轨道交通规划、组织优化等方面为我国经济社会发展做出了突出贡献。研究成果在铁路运输组织、客运专线规划与运营、城际轨道交通运营组织中得到良好应用。
研究所继续将面向轨道交通主战场，致力于推进运营组织优化基础理论研究、成果转化和应用的步伐，加强营运组织管理决策系统的开发，继续为轨道交通运营科学化、信息化、自动化的发展做出贡献。