Ravelijn

prof.dr.ir. M.R.K. Mes (Martijn)

Full Professor
BMS-HBE-IEMS
Ravelijn 3414
m.r.k.mes@utwente.nl
+31534894062
Business card

Martijn Mes is a full professor of Transportation and Logistics Management (TLM) 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 PhD at the School of Management and Governance, University of Twente (2008). After finishing his PhD, 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 optimization and artificial intelligence for transportation and logistics management. Three application areas can be distinguished within this domain: (i) emergency logistics, (ii) urban logistics, and (iii) sustainable logistics. Within these application areas, Martijn focusses on (i) the use of AI for logistics management (supporting strategic, tactical and operational logistics decision-making) and (ii) the use of autonomous or electric vehicles (e.g., drones, delivery robots, AGVs, autonomous trucks). More specifically, Martijn uses quantitative modelling techniques, from the Artificial Intelligence and Operations Research domains, such as stochastic optimization (Approximate Dynamic Programming, Optimal Learning, Machine Learning, Deep Reinforcement Learning), simulation (discrete-event simulation, simulation optimization), multi-agent systems, and serious gaming. Martijn participated in various research and implementation projects (national as well as European) on the topics of sustainable logistics, urban logistics, city distribution, port logistics, and intermodal/synchromodal transport. Within the program Industrial Engineering and Management, Martijn provides various BSc and MSc courses related to simulation, queueing theory, Markov chains, dynamic programming, approximate dynamic programming, reinforcement learning, transportation management, and management of technology.

Expertise

  • Computer Science

    • Dynamic Programming
    • Vehicle Routing
    • Case Study
    • Simulation Model
    • Problem Instance
    • Approximation (Algorithm)
    • Service Provider

  • Social Sciences

    • Transport

Organisations

Publications

Jump to: 2026 | 2025 | 2024

2026

From gate to runway: A systematic review of airport ground operations optimization (2026)Journal of Air Transport Management, 135. Article 103013. Dahanayaka, M., Prak, D. & Mes, M.https://doi.org/10.1016/j.jairtraman.2026.103013A discrete-event simulation framework for smart logistics nodes with agent-based control of hub-to-hub transport (2026)Simulation Modelling Practice and Theory, 150. Article 103284. Brunetti, M., Lalla-Ruiz, E. & Mes, M.https://doi.org/10.1016/j.simpat.2026.103284Rethinking innovation theory through collaborative innovation platforms: Synthesising a taxonomy of innovation mechanisms using a multi-vocal literature review (2026)Journal of Open Innovation: Technology, Market, and Complexity, 12(2). Article 100794. Pertenbreiter, M., Sedrakyan, G., Mes, M. & Piest, J. P. S.https://doi.org/10.1016/j.joitmc.2026.100794Risk management in digital finance: Assessment and pricing in an emerging fintech era (2026)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Baals, L. J.https://doi.org/10.3990/1.9789036571234Efficient Road Renovation Scheduling under Uncertainty using Lower Bound Pruning (2026)[Working paper › Preprint]. ArXiv.org. Bosch, R., Rogetzer, P., van Heeswijk, W. & Mes, M.https://doi.org/10.48550/arXiv.2602.15554Self-Organization in Crowd-Sourced Food Delivery Systems (2026)In 2025 Winter Simulation Conference, WSC 2025 (pp. 175-187) (Proceedings of the Winter Simulation Conference; Vol. 2025). IEEE. Gerrits, B. & Mes, M.https://doi.org/10.1109/WSC68292.2025.11339016Enhancing Electric Interterminal Transport: A Truck Decoupling System With Early Information on Arrivals (2026)Journal of advanced transportation, 2026(1). Article 8968454. Brunetti, M., Lalla-Ruiz, E. & Mes, M.https://doi.org/10.1155/atr/8968454

2025

Deep Learning–Accelerated Multi-Start Large Neighborhood Search for Real-time Freight Bundling (2025)[Working paper › Preprint]. ArXiv.org. Zhang, H., van Heeswijk, W., Hu, X., Yorke-Smith, N. & Mes, M.https://doi.org/10.48550/arXiv.2512.11187Optimizing autonomous multimodal last-mile delivery systems with time windows: Analyzing trade-offs between drones, robots, and trucks (2025)Transportation research. Part E: Logistics and transportation review, 204. Article 104427. Campuzano, G., Lalla-Ruiz, E. & Mes, M.https://doi.org/10.1016/j.tre.2025.104427Smart Logistics Nodes: Connected Automated Transport for Future-Proof Ports and Business Parks (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Brunetti, M.https://doi.org/10.3990/1.9789036566865Anticipatory scheduling of synchromodal transport using approximate dynamic programming (2025)Annals of operations research, 350(1), 95–129. Rivera, A. E. P. & Mes, M. R. K.https://doi.org/10.1007/s10479-022-04668-6Distance approximation to support customer selection in vehicle routing problems (2025)Annals of operations research, 350(1), 269-297. Akkerman, F. & Mes, M.https://doi.org/10.1007/s10479-022-04674-8Optimization and artificial intelligence in logistics management (2025)Annals of operations research, 350(1), 1-3. Lalla-Ruiz, E. & Mes, M. R. K.https://doi.org/10.1007/s10479-025-06700-xRequirements Analysis for a Digital Twin to Increase the Resilience of Multimodal Corridors: A Case Study in the Twente Region (2025)In Advanced Information Systems Engineering Workshops - CAiSE 2025 Workshops, Proceedings (pp. 219-230) (Lecture Notes in Business Information Processing; Vol. 556 LNBIP). Springer. Guizzardi - Silva Souza, R., Piest, J. P. S., Akyazi, A., Ariji, S., Tao, T., Bastani, M., Scheijgrond, A. R., Kromanis, R., Vahdatikhaki, F., Hüllmann, J. A. & Mes, M.https://doi.org/10.1007/978-3-031-94931-9_18Machine Learning Predictions for Traffic Equilibria in Road Renovation Scheduling (2025)[Working paper › Preprint]. ArXiv.org. Bosch, R., van Heeswijk, W., Rogetzer, P. & Mes, M.https://doi.org/10.48550/arXiv.2506.05933The selective multiple depot pickup and delivery problem with multiple time windows and paired demand (2025)Operations Research Perspectives, 14. Article 100342. Roelink, D., Campuzano, G., Mes, M. & Lalla-Ruiz, E.https://doi.org/10.1016/j.orp.2025.100342The two-tier multi-depot vehicle routing problem with robot stations and time windows (2025)Engineering applications of artificial intelligence, 147. Article 110258. Campuzano, G., Lalla-Ruiz, E. & Mes, M.https://doi.org/10.1016/j.engappai.2025.110258Solving dual sourcing problems with supply mode dependent failure rates (2025)International journal of production research (E-pub ahead of print/First online). Akkerman, F., Knofius, N., van der Heijden, M. & Mes, M.https://doi.org/10.1080/00207543.2025.2489755Solving Dual Sourcing Problems with Supply Mode Dependent Failure Rates (2025)[Working paper › Preprint]. ArXiv.org. Akkerman, F., Knofius, N., van der Heijden, M. & Mes, M.https://doi.org/10.48550/arXiv.2410.03887Machine Learning for Sequential Decisions in Logistics (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Akkerman, F. R.https://doi.org/10.3990/1.9789036565349Dynamic reordering and inspection for the multi-item Inventory Record Inaccuracy problem (2025)European journal of operational research, 321(2), 428-444. Akkerman, F., Prak, D. & Mes, M.https://doi.org/10.1016/j.ejor.2024.09.033Learning Dynamic Selection and Pricing of Out-of-Home Deliveries (2025)Transportation science, 59(2), 207-450. Akkerman, F., Dieter, P. & Mes, M.https://doi.org/10.1287/trsc.2023.0434The Stochastic Dynamic Postdisaster Inventory Allocation Problem with Trucks and UAVs (2025)Transportation science, 59(2), 360-390. van Steenbergen, R. M., van Heeswijk, W. J. A. & Mes, M. R. K.https://doi.org/10.1287/trsc.2023.0438A comparison of reinforcement learning policies for dynamic vehicle routing problems with stochastic customer requests (2025)Computers & industrial engineering, 200. Article 110747. Akkerman, F., Mes, M. & van Jaarsveld, W.https://doi.org/10.1016/j.cie.2024.110747

2024

Circular Construction Ecosystems: Designing a Circularity Information Platform for the Built Environment (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Yu, Y.https://doi.org/10.3990/1.9789036563970

Research profiles

Courses academic year 2026/2027

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 2025/2026

Courses academic year 2024/2025

QR codeScan the QR code or
Download vCard