Ravelijn

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

Hoogleraar
BMS-HBE-IEMS
Ravelijn 3414
m.r.k.mes@utwente.nl
+31534894062
Visitekaartje

Martijn Mes is hoogleraar Transport en Logistiek Management (TLM) binnen de vakgroep High Tech Business and Entrepreneurship (HBE) aan de Universiteit Twente. Hij behaalde in 2002 zijn masterdiploma Toegepaste Wiskunde en promoveerde in 2008 aan de School of Management and Governance van de Universiteit Twente. Na afronding van zijn promotieonderzoek werkte Martijn als postdoc bij Princeton University, vakgroep Operations Research and Financial Engineering (ORFE), waar hij onderzoek deed naar Ranking and Selection (R&S), Bayesian Global Optimization (BGO) en Optimal Learning. In brede zin richt Martijns onderzoek zich op optimalisatie en artificiĂ«le intelligentie voor transport- en logistiekmanagement. Binnen dit domein kunnen drie toepassingsgebieden worden onderscheiden: (i) nood- en crisislogistiek, (ii) stedelijke logistiek en (iii) duurzame logistiek. Binnen deze gebieden focust Martijn zich op (i) het gebruik van AI voor logistiek management, ter ondersteuning van strategische, tactische en operationele besluitvorming, en (ii) het gebruik van autonome en elektrische voertuigen, zoals drones, bezorgrobots, AGV’s en autonome vrachtwagens. Meer specifiek maakt Martijn gebruik van kwantitatieve modelleertechnieken uit de domeinen artificiĂ«le intelligentie en operations research, waaronder stochastische optimalisatie (Approximate Dynamic Programming, Optimal Learning, Machine Learning en Deep Reinforcement Learning), simulatie (discrete-event simulatie en simulatie-optimalisatie), multi-agent systemen en serious gaming. Martijn heeft deelgenomen aan uiteenlopende nationale en Europese onderzoeks- en implementatieprojecten op het gebied van duurzame logistiek, stedelijke logistiek, stadsdistributie, havenlogistiek en intermodaal en synchromodaal transport. Binnen de opleiding Industrial Engineering and Management verzorgt Martijn verschillende bachelor- en mastervakken op het gebied van simulatie, wachtrijtheorie, Markov-ketens, dynamisch programmeren, approximate dynamic programming, reinforcement learning, transportmanagement en technology management.

Expertises

  • Computer Science

    • Simulation
    • Models
    • Dynamic Programming
    • Heuristics
    • Vehicle Routing

  • Social Sciences

    • Problem
    • Approach
    • Logistics

Organisaties

Publicaties

Jump to: 2026 | 2025 | 2024

2026

Risk 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/10.3990/1.9789036571234From gate to runway: A systematic review of airport ground operations optimization (2026)Journal of Air Transport Management, 135. Article 103013 (E-pub ahead of print/First online). Dahanayaka, M., Prak, D. & Mes, M.https://doi.org/10.1016/j.jairtraman.2026.103013Efficient 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). 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/10.3990/1.9789036563970Smart logistics nodes: concept and classification (2024)International Journal of Logistics Research and Applications, 27(11), 1984-2020. Brunetti, M., Mes, M. & Lalla-Ruiz, E.https://doi.org/10.1080/13675567.2024.2327394Design Implications for Integrating AI Chatbot Technology with Learning Management Systems: A Study-based Analysis on Perceived Benefits and Challenges in Higher Education (2024)In ICAITE 2024: Proceedings of the 2024 International Conference on Artificial Intelligence and Teacher Education (pp. 1-8). ACM Press. Sedrakyan, G., Borsci, S., Machado, M., Rogetzer, P. & Mes, M.https://doi.org/10.1145/3702386.3702405

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