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

Martijn Mes is hoogleraar transport en logistiek management (TLM) en voorzitter van de vakgroep Industrial Engineering en Business Information Systems (IEBIS) van de Universiteit Twente (UT). Hij haalde zijn mastertitel Toegepaste Wiskunde (2002), deed zijn promotieonderzoek bij de faculteit Management and Governance bij de UT (2008) en zijn postdoc aan Princeton University (2009). Martijn is actief op de volgende gebieden: goederenvervoer, synchromodaal transport, multi-agent systems (MAS), beprijzing van transport en elektronische marktplaatsen voor transport, dynamische voertuigroutering (VRP & DVRP), ranking and selection problems (R&S), optimal learning en kunstmatige intelligentie, approximate dynamic programming (ADP), simulation optimization, discrete-event simulation, en simulatie van logistieke systemen. Martijn heeft meegewerkt aan een groot aantal onderzoek- en implementatieprojecten (nationaal en Europees) op het gebied van duurzaam transport, stadslogistiek en stadsdistributie, synchromodaal en intermodaal transport, havenlogistiek en zorglogistiek. Martijn verzorgt diverse bachelor- en mastervakken op het gebied van computersimulatie, wachtrijtheorie, (stochastisch) dynamisch programmeren, Markov ketens, mathematisch programmeren, transport management, en management van technologie.

Kijk op mijn persoonlijke pagina voor meer informatie.

Engineering & Materials Science

# Consolidation
# Costs
# Dynamic Programming
# Logistics
# Pickups
# Planning
# Vehicle Routing

Business & Economics

# Approximate Dynamic Programming

Faculty of Behavioural, Management and Social Sciences (BMS), Industrial Engineering & Business Information Systems (IEBIS)

van Steenbergen, R. M. , Mes, M. , & van Heeswijk, W. J. A. (2023). Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty. Transportation Research Part C: Emerging Technologies, 157, Article 104401. Advance online publication. https://doi.org/10.1016/j.trc.2023.104401

Koot, M. , Mes, M. R. K. , & Iacob, M. E. (2024). Building an Ontological Bridge Between Supply Chain Resilience and IoT Applications. In H. A. Proper, L. Pufahl, D. Karastoyanova, M. van Sinderen, & J. Moreira (Eds.), Enterprise Design, Operations, and Computing: 27th International Conference, EDOC 2023, Groningen, The Netherlands, October 30 – November 3, 2023, Proceedings (1 ed., pp. 79-96). (Lecture Notes in Computer Science). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-46587-1_5

Morim, A., Campuzano, G., Amorim, P. , Mes, M. , & Lalla-Ruiz, E. (2024). The drone-assisted vehicle routing problem with robot stations. Expert systems with applications, 238, Article 121741. Advance online publication. https://doi.org/10.1016/j.eswa.2023.121741

Pourmehdi, M. , Iacob, M. E. , & Mes, M. R. K. (2023). Towards a Reference Architecture for Planning and Control Services. In C. Griffo, S. Guerreiro, & M. E. Iacob (Eds.), Advances in Enterprise Engineering XVI: 12th Enterprise Engineering Working Conference, EEWC 2022, Revised Selected Papers (1 ed., pp. 121-138). (Lecture Notes in Business Information Processing; Vol. 473 LNBIP). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-34175-5_8

Geevers, K., van Hezewijk, L. , & Mes, M. R. K. (2023). Multi-echelon inventory optimization using deep reinforcement learning. Central European journal of operations research. Advance online publication. https://doi.org/10.1007/s10100-023-00872-2

Bosch, R. , Rogetzer, P. , van Heeswijk, W. J. A. , & Mes, M. (2023). Scheduling Urban Infrastructure Renovation Projects to Minimize Traffic Disruption. In 14th International Conference on Computational Logistics

van Steenbergen, R. M. , Lalla-Ruiz, E. , van Heeswijk, W. J. A. , & Mes, M. (2023). The Heterogeneous Fleet Risk-Constrained Vehicle Routing Problem in Humanitarian Logistics. In J. R. Daduna, G. Liedtke, X. Shi, & S. Voß (Eds.), Computational Logistics: 14th International Conference, ICCL 2023, Berlin, Germany, September 6–8, 2023, Proceedings (pp. 276-291). (Lecture Notes in Computer Science; Vol. 14239). Springer. https://doi.org/10.1007/978-3-031-43612-3_17

Gerrits, B. , Mes, M. , Schuur, P., & Andringa, R. (2023). A Simulation Model for Cooperative Robotics in Dairy Farms. In B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C. G. Corlu, L. H. Lee, E. P. Chew, T. Roeder, & P. Lendermann (Eds.), 2022 Winter Simulation Conference (WSC) (pp. 831-842). (Proceedings - Winter Simulation Conference; Vol. 2022-December). IEEE. https://doi.org/10.1109/WSC57314.2022.10015409

Campuzano, G. , Lalla-Ruiz, E. , & Mes, M. (2023). The drone-assisted variable speed asymmetric traveling salesman problem. Computers & industrial engineering, 176, Article 109003. https://doi.org/10.1016/j.cie.2023.109003

Boschma, R. , Mes, M. R. K. , & de Vries, L. R. (2023). Approximate dynamic programming for container stacking. European journal of operational research, 310(1), 328-342. Advance online publication. https://doi.org/10.1016/j.ejor.2023.02.034

Gerrits, B. (2023). Self-Organizing Logistics: Towards a Unifying Framework for Automated Transport Systems. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036555555

Eikenbroek, O. A. L. (2023). Variations in Urban Traffic. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789055843213

Brunetti, M., Campuzano, G. , & Mes, M. (2023). Simulation of the Internal Electric Fleet Dispatching Problem at a Seaport: A Reinforcement Learning Approach. In B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C. G. Corlu, L. H. Lee, E. P. Chew, T. Roeder, & P. Lendermann (Eds.), 2022 Winter Simulation Conference (pp. 2675-2686). (Proceedings - Winter Simulation Conference; Vol. 2022-December). IEEE. https://doi.org/10.1109/WSC57314.2022.10015516

Rivera, A. E. P. , & Mes, M. R. K. (2022). Anticipatory scheduling of synchromodal transport using approximate dynamic programming. Annals of operations research. Advance online publication. https://doi.org/10.1007/s10479-022-04668-6, https://doi.org/10.1007/s10479-022-04668-6

Campuzano, G. , Lalla-Ruiz, E. , & Mes, M. (2022). The Dynamic Drone Scheduling Delivery Problem. In J. de Armas, H. Ramalhinho, & S. Voß (Eds.), Computational Logistics - 13th International Conference, ICCL 2022, Proceedings (pp. 260-274). (Lecture Notes in Computer Science; Vol. 13557). Springer. https://doi.org/10.1007/978-3-031-16579-5_18

Akkerman, F. , Mes, M., & van Jaarsveld, W. (2022). A Comparison of Reinforcement Learning Policies for Dynamic Vehicle Routing Problems with Stochastic Customer Requests.

Akkerman, F. , Mes, M. , & Lalla-Ruiz, E. (2022). Dynamic Time Slot Pricing Using Delivery Costs Approximations. In J. de Armas, H. Ramalhinho, & S. Voß (Eds.), Computational Logistics: 13th International Conference, ICCL 2022, Barcelona, Spain, September 21–23, 2022, Proceedings (pp. 214–230). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13557 LNCS). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-16579-5_15

Akkerman, F. , Lalla-Ruiz, E. , Mes, M., & Spitters, T. (2022). Cross-Docking: Current Research Versus Industry Practice and Industry 4.0 Adoption. In T. Bondarouk, & M. R. Olivas-Luján (Eds.), Smart Industry - Better Management (pp. 69-104). (Advanced Series in Management; Vol. 28). Emerald. https://doi.org/10.1108/S1877-636120220000028007

Asadi, A., Pinkley, S. N. , & Mes, M. (2022). A Markov decision process approach for managing medical drone deliveries. Expert systems with applications, 204, Article 117490. Advance online publication. https://doi.org/10.1016/j.eswa.2022.117490

Akkerman, F. , & Mes, M. (2022). Distance approximation to support customer selection in vehicle routing problems. Annals of operations research. Advance online publication. https://doi.org/10.1007/s10479-022-04674-8

Castiglione, C. , Yazan, D. M., Alfieri, A. , & Mes, M. (2021). A holistic technological eco-innovation methodology for industrial symbiosis development. Sustainable Production and Consumption, 28, 1538-1551. Advance online publication. https://doi.org/10.1016/j.spc.2021.09.002

van Steenbergen, R. M., Brunetti, M. , & Mes, M. (2021). Network Generation for Simulation of Multimodal Logistics Systems. In 2021 Winter Simulation Conference (WSC) IEEE. https://doi.org/10.1109/WSC52266.2021.9715497

Mes, M. , Lalla-Ruiz, E., & Voß, S. (2021). Preface. In Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. v-vi). (Lecture Notes in Computer Science; Vol. 13004).

Gil, A. F. , Lalla-Ruiz, E. , Mes, M., & Castro, C. (2021). Optimization of Green Pickup and Delivery Operations in Multi-depot Distribution Problems. In M. Mes, E. Lalla-Ruiz, & S. Voß (Eds.), Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. 487-501). (Lecture Notes in Computer Science; Vol. 13004). Springer. https://doi.org/10.1007/978-3-030-87672-2_32

Campuzano, G. , Lalla-Ruiz, E. , & Mes, M. (2021). A Multi-start VNS Algorithm for the TSP-D with Energy Constraints. In M. Mes, E. Lalla-Ruiz, & S. Voß (Eds.), Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. 393-409). (Lecture Notes in Computer Science; Vol. 13004). Springer. https://doi.org/10.1007/978-3-030-87672-2_26

Bekijk alle publicaties van deze medewerker

Naar mijn profiel

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.