学科方向设置：
（1）管理决策与优化。面向管理科学与工程学科内涵，通过探究复杂系统统计数据分析模型与方法、复杂系统脆弱性治理理论与方法、不确定环境下的管理决策理论与方法等，致力于多场景、多主体、多模式的复杂系统优化、决策、风险管控与效率提升，在复杂公共交通系统脆弱性治理与优化、基于人工智能技术的复杂系统决策建模与求解、复杂物流与供应链系统决策优化与算法设计等方面为研究生奠定扎实的研究基础。
（2）数据科学与智能管理。面向“新基建”“交通强国”等国家重大战略和需求，立足于智能交通运输服务，以供需价值链为主线，系统探究综合运输结构优化、服务供需管理与决策、交通脆弱性评估与治理等问题，力争在基于大数据的交通运输服务需求与供给管理、综合运输体系结构优化理论与方法、运输工程管理与决策理论及方法、城市公共交通系统韧性及脆弱性提升等具体研究领域培养创新与应用“复合型”人才。
（3）物流与交通管理。面向共建“一带一路”、建设“交通强国”、保障“供应链安全”等国家重大战略需求，以物流基础设施规划及其运营管理为基础，衔接供应链协作优化与风险控制，探索复杂情景下的物流与供应链网络高效、安全运行理论与方法，突出信息技术支持下的物流智能运作和智慧管理，力争在基于大数据的物流网络设计与优化、物流产业发展规划、物流与供应链金融、供应链安全与绿色管理等方面培养一批高水平研究型人才。
（4）工程管理。面向“新基建”“中国建造2035”等国家重大战略和需求，以交通基础设施和重大建设工程为依托，研究复杂动态情境下工程项目全生命周期管理理论与方法，突出数字孪生视角下的绿色智能管理，力争在复杂工程集成控制、工程大数据驱动的智能决策、工程全生命周期业务协调优化、工程项目管理与节能减排等方面培养创新型研究人才。
Discipline orientation:
(1) Management Decision-Making and Optimization. Aligned with the core of Management Science and Engineering, this discipline explores statistical analysis models and methodologies for complex systems, theories and approaches for managing complex system fragility, and decision-making theories and methods under uncertainty. It focuses on optimizing complex systems, decision-making, risk management, and efficiency enhancement across diverse scenarios, stakeholders, and operational modes. This discipline establishes a robust research foundation for postgraduate students in areas including vulnerability governance and optimization within complex public transport systems, decision modelling and solution techniques for complex systems leveraging artificial intelligence, and decision optimization and algorithm design for complex logistics and supply chain systems.
(2) Data Science and Intelligent Management. Aligned with national strategic priorities such as the ‘New Infrastructure’ initiative and the ‘Transportation Powerhouse’ strategy, this discipline focuses on intelligent transport services. Centred on the supply-demand value chain, it explores issues including: systematically exploring issues such as integrated transport structure optimization, service supply-demand management and decision-making, and transport vulnerability assessment and governance. It aims to cultivate innovative and applied ‘composite’ talents in specific research domains including big data-driven transport service demand and supply management, theories and methods for optimizing integrated transport system structures, transport engineering management and decision-making theories and methodologies, and enhancing the resilience and vulnerability of urban public transport systems.
(3) Logistics and Transport Management. Addressing major national strategic requirements such as ‘Jointly Building the Belt and Road’, establishing ‘A country with strong transportation network', and safeguarding 'Supply Chain Security', this discipline integrates logistics infrastructure planning and operational management with integrating supply chain collaboration optimization with risk control. We explore theories and methodologies for the efficient and secure operation of logistics and supply chain networks under complex scenarios, emphasizing intelligent logistics operations and smart management supported by information technology. Our aim is to cultivate a cohort of high-calibre research-oriented talents in areas including big data-driven logistics network design and optimization, logistics industry development planning, logistics and supply chain finance, and supply chain security and green management.
(4) Engineering Management. Aligned with national strategic priorities such as the ‘New Infrastructure’ initiative and ‘China Construction 2035’, this discipline leverages transport infrastructure and major construction projects to investigate theories and methodologies for managing engineering projects throughout their entire lifecycle within complex dynamic contexts. Emphasis is placed on green and intelligent management through the lens of digital twins, aiming to cultivate innovative research talent in areas including integrated control of complex engineering systems, engineering big data-driven intelligent decision-making, optimization of engineering lifecycle coordination, and engineering project management integrated with energy conservation and emissions reduction.
