Martijn Mes is a full professor of Transportation and Logistics Management (TLM) and chair of the Industrial Engineering and Business Information Systems (IEBIS) section within the High Tech Business and Entrepreneurship (HBE) department at the University of Twente (Enschede, The Netherlands). He holds a master’s degree in Applied Mathematics (2002) and did his Ph.D. at the School of Management and Governance, University of Twente (2008). After finishing his Ph.D., Martijn did his postdoc at Princeton University, Department of Operations Research and Financial Engineering, where he did research on the topics of Ranking and Selection (R&S), Bayesian Global Optimization (BGO), and Optimal Learning. In general, Martijn's research involves freight transportation, synchromodal transport, multi-agent systems (MAS), pricing and auctions in freight transport, dynamic vehicle routing problems (VRP & DVRP), ranking and selection problems (R&S), optimal learning, approximate dynamic programming (ADP), simulation optimization, discrete-event simulation, and simulation of logistics and healthcare systems. Martijn participated in various research and implementation projects (national as well as European) on the topics of sustainable logistics, urban logistics, city distribution, healthcare logistics, port logistics, and intermodal and synchromodal transport. Within the program Industrial Engineering and Management, Martijn provides various BSc and MSc courses related to simulation, queueing theory, (stochastic) dynamic programming, Markov chains, mathematical programming, transportation management, and technology management.

For more information, see my personal page.


  • Computer Science

    • Simulation
    • Models
    • Dynamic Programming
    • Heuristics
  • Social Sciences

    • Problem
    • Approach
    • Logistics
    • Time



Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty, Article 104401. van Steenbergen, R. M., Mes, M. & van Heeswijk, W. J. A. dynamic programming for container stacking, 328-342. Boschma, R., Mes, M. R. K. & de Vries, L. R. Heterogeneous Fleet Risk-Constrained Vehicle Routing Problem in Humanitarian LogisticsIn Computational Logistics: 14th International Conference, ICCL 2023, Berlin, Germany, September 6–8, 2023, Proceedings (pp. 276-291). Springer. van Steenbergen, R. M., Lalla-Ruiz, E., van Heeswijk, W. J. A. & Mes, M. Urban Infrastructure Renovation Projects to Minimize Traffic DisruptionIn 14th International Conference on Computational Logistics. Bosch, R., Rogetzer, P., van Heeswijk, W. J. A. & Mes, M.Multi-echelon inventory optimization using deep reinforcement learning (E-pub ahead of print/First online). Geevers, K., van Hezewijk, L. & Mes, M. R. K. a Reference Architecture for Planning and Control ServicesIn Advances in Enterprise Engineering XVI: 12th Enterprise Engineering Working Conference, EEWC 2022, Revised Selected Papers (pp. 121-138). Springer (E-pub ahead of print/First online). Pourmehdi, M., Iacob, M. E. & Mes, M. R. K. Logistics: Towards a Unifying Framework for Automated Transport Systems. University of Twente. Gerrits, B. in Urban Traffic. University of Twente. Eikenbroek, O. A. L. drone-assisted variable speed asymmetric traveling salesman problem, Article 109003. Campuzano, G., Lalla-Ruiz, E. & Mes, M. of the Internal Electric Fleet Dispatching Problem at a Seaport: A Reinforcement Learning ApproachIn 2022 Winter Simulation Conference (pp. 2675-2686). IEEE. Brunetti, M., Campuzano, G. & Mes, M. Simulation Model for Cooperative Robotics in Dairy FarmsIn 2022 Winter Simulation Conference (WSC) (pp. 831-842). IEEE. Gerrits, B., Mes, M., Schuur, P. & Andringa, R.
A Markov decision process approach for managing medical drone deliveries, Article 117490. Asadi, A., Pinkley, S. N. & Mes, M. Dynamic Drone Scheduling Delivery ProblemIn Computational Logistics - 13th International Conference, ICCL 2022, Proceedings (pp. 260-274). Springer. Campuzano, G., Lalla-Ruiz, E. & Mes, M. Comparison of Reinforcement Learning Policies for Dynamic Vehicle Routing Problems with Stochastic Customer Requests (In preparation). Akkerman, F., Mes, M. & van Jaarsveld, W.Cross-Docking: Current Research Versus Industry Practice and Industry 4.0 AdoptionIn Smart Industry - Better Management (pp. 69-104). Emerald. Akkerman, F., Lalla-Ruiz, E., Mes, M. & Spitters, T. scheduling of synchromodal transport using approximate dynamic programming (E-pub ahead of print/First online). Rivera, A. E. P. & Mes, M. R. K. approximation to support customer selection in vehicle routing problems (E-pub ahead of print/First online). Akkerman, F. & Mes, M. Time Slot Pricing Using Delivery Costs ApproximationsIn Computational Logistics: 13th International Conference, ICCL 2022, Barcelona, Spain, September 21–23, 2022, Proceedings (pp. 214–230). Springer. Akkerman, F., Mes, M. & Lalla-Ruiz, E.
A holistic technological eco-innovation methodology for industrial symbiosis development, 1538-1551. Castiglione, C., Yazan, D. M., Alfieri, A. & Mes, M. Multi-start VNS Algorithm for the TSP-D with Energy ConstraintsIn Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. 393-409). Springer. Campuzano, G., Lalla-Ruiz, E. & Mes, M.

Research profiles

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

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