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Dr David Lai

David

Associate Professor in Operations Management

Email: david.lai@qmul.ac.uk
Room Number: Room 3.28C, Francis Bancroft Building, Mile End Campus
Website: https://www.linkedin.com/in/davidswlai
Office Hours: Wednesday 2pm – 5pm (by email appointment)

Profile

Roles

Biography:

Dr David Lai is an Associate Professor (Senior Lecturer) of Operations Management at Queen Mary University of London (QMUL). Prior to joining QMUL, David worked as an Assistant Professor at the University of Southampton (2022–2024), Eindhoven University of Technology (2020–2022), and VU Amsterdam (2014–2020). He obtained his PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong in 2014.

Teaching

Postgraduate:

  • BUSM227-C24 Transportation and Logistics Analytics
  • BUSM221-C24 Capstone Project in Supply Chain and Logistics Analytics

 

Research

Research Interests:

David’s research interests are in Operations Research and Logistics Analytics, with recent publications covering areas such as vehicle routing, green logistics, staff rostering, inventory optimisation, production planning, and multimodal transportation. He uses methods from network and integer programming, metaheuristics, simulation, combinatorial optimization, and machine learning.

Centre and Group Membership:

Publications

  • Lai, D. S., Costa, Y., Demir, E., Florio, A. M., & Van Woensel, T. (2024). The pollution-routing problem with speed optimization and uneven topography. Computers & Operations Research, 164, 106557.
  • Lai, D. S., Li, Y., Demir, E., Dellaert, N., & Van Woensel, T. (2022). Self-adaptive randomized constructive heuristics for the multi-item capacitated lot sizing problem. Computers & Operations Research, 147, 105928.
  • Lai, D. S., Leung, J. M., Dullaert, W., & Marques, I. (2020). A graph-based formulation for the shift rostering problem. European Journal of Operational Research, 284(1), 285-300.
  • Hoogeboom, M., Dullaert, W., Lai, D. S., & Vigo, D. (2020). Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows. Transportation Science, 54(2), 400-416.
  • Dabia, S., Lai, D. S., & Vigo, D. (2019). An exact algorithm for a rich vehicle routing problem with private fleet and common carrier. Transportation Science, 53(4), 986-1000.
  • Noordhoek, M., Dullaert, W., Lai, D. S., & de Leeuw, S. (2018). A simulation–optimization approach for a service-constrained multi-echelon distribution network. Transportation Research Part E: Logistics and Transportation Review, 114, 292-311.
  • Lai, D. S., & Leung, J. M. (2018). Real-time rescheduling and disruption management for public transit. Transportmetrica B: Transport Dynamics, 6(1), 17-33.
  • Lai, D. S., Demirag, O. C., & Leung, J. M. (2016). A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph. Transportation Research Part E: Logistics and Transportation Review, 86, 32-52.

Supervision

Areas of supervision expertise

Dr David Lai welcomes applications from prospective PhD students interested in logistics and supply chain optimization, with a focus on areas such as vehicle routing, capacitated network design, staff scheduling, and multi-echelon inventory optimisation. The research will emphasise the application of exact and heuristic methods from Operational Research to address complex real-life challenges.

Current doctoral students

  • Dawei Chen, Deep Reinforcement Learning in Transportation Research (since 2021)
  • Suheyb Erdemci, Exact and heuristic methods for the Vehicle Routing Problems (since 2023)
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