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Dr Zhiyuan Lin

Dr Zhiyuan Lin

  • Position: Lecturer in Railway Operations and Control
  • Areas of expertise: Transport scheduling, esp. train timetabling and rolling stock / crew scheduling; Operational Research and network flow optimisation; Efficient solution approaches for integer linear programs.
  • Email: Z.Lin@leeds.ac.uk
  • Phone: +44(0)113 343 7410
  • Location: 2.01 ITS

Profile

I have a background in Operational Research (OR), Computational Optimisation and Computer Science. Before joining ITS, Leeds, I was a research fellow at School of Computing, University of Leeds, and then a lecturer at Alliance Manchester Business School, University of Manchester.

I belong to the Spatial Modelling and Dynamics (SMaD) group of ITS.

Responsibilities

  • Module leader of TRAN5510M Railway Operations and Management
  • MSc student personal tutor

Research interests

Key research interest:

  • Railway scheduling, including timetabling, rolling stock scheduling and crew scheduling
  • The application of Operational Research (OR) and optimisation (esp. combinatorial optimisation and network flow problems) in various transport problems
  • Advanced algorithms for integer linear programming, including both exact and meta/hybrid heuristic methods
  • Machine learning based approaches in transport optimisation

Research projects (past and ongoing):

  • Innovate UK / Rail Safety and Standards Board (RSSB): Dynamic train planning: Very Short Term Planning (VSTP)
  • EU Horizon 2020 - Innovation Actions: MOdify Drivers’ behaviour to Adapt for Lower EmissionS (MODALES) https://modales-project.eu/
  • EU Horizon 2020: Roadmaps for A.I. Integration in the Rail Sector (RAILS) https://rails-project.eu/ 
  • Ministry of Science, Innovation and Universities (Spain): Mathematical Optimization in Network Location and Planning Problems https://investigacion.us.es/sisius/sis_proyecto.php?idproy=32145 
  • UK EPSRC: Train Unit Scheduling Optimisation https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/M007243/1 
  • UK EPSRC: Assessing the underworld - an integrated performance model of city infrastructures
  • UK EPSRC: Mapping the Underworld
  • EU and the Ministry of Economy and Competitiveness (Spain): Structural analysis of mathematical models for optimization in location and transportation planning
  • Alliance Manchester Business School: Assessing train timetable robustness by supervised machine learning

PhD student supervision:

  • Li Lei (School of Computing, completed)
  • Ruifan Tang (2020 – )
  • Jinyi Pan (2022 – )
  • Youxin Lin (School of Civil Engineering, 2022 – )
  • Chuhan Yin (2023 – )

Visiting PhDs/scholars:

  • Enze Liu (2022 – )
  • Peiyang Wu (2022 – ) 
  • Fei Han (2022 – )
  • Xue Wu (2022 – ) 
<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://environment.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>

Qualifications

  • PhD Computer Science, School of Computing, University of Leeds, UK

Professional memberships

  • Honorary member of Decision and Cognitive Sciences Research Centre, University of Manchester

Student education

  • I presently teach modules:
    • TRAN5510M Railway Operations & Management (module lead)
    • TRAN5550M Railway Signalling and Control
    • TRAN5020M Principles of Transport Modelling
    • TRAN3031 Public Transport Policy and Practice 
    • TRAN5181M Public Transport Planning and Management
  • TRAN5912M Transport Integrated Project (TIP): Student mentor and area expert
  • MSc student project supervisor and academic personal tutor

Research groups and institutes

  • Spatial Modelling and Dynamics

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>