Martijn Mes

prof. Dr. ir. M.R.K. Mes

University of Twente
Faculty of Behavioural Management and Social Sciences
Dep. Industrial Engineering and Business Information Systems

P.O. Box 217
7500 AE Enschede
The Netherlands

Room: RA 3414 (Ravelijn)
Tel: (+31 53 489)4062
Fax: (+31 53 489)2159
E-mail: m.r.k.mes@utwente.nl

Summary

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 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 focuses 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 modeling 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.

Research interests

Publications

Refereed publications:  

  1. F. Akkerman, Martijn Mes, Willem van Jaarsveld (2025). A comparison of reinforcement learning policies for dynamic vehicle routing problems with stochastic customer requests. Computers & Industrial Engineering. [https://doi.org/10.1016/j.cie.2024.110747]
  2. F. Akkerman, P. Dieter, M.R.K. Mes (2024). Learning Dynamic Selection and Pricing of Out‑of‑Home Deliveries. Transportation Science. [https://doi.org/10.1287/trsc.2023.0434]
  3. F. Akkerman, D. Prak, M.R.K. Mes (2024). Dynamic Reordering and Inspection for the Multi-item Inventory Record Inaccuracy Problem. European Journal of Operational Research. [https://doi.org/10.1016/j.ejor.2024.09.033]
  4. M. Brunetti, E. Lalla-Ruiz, M.R.K. Mes (2024). Enhancing Inter-Terminal Transport via Early Information. In: Emrouznejad et al. (eds) Business Analytics and Decision Making in Practice. ICBAP 2024. Lecture Notes in Operations Research. Springer, Cham. [https://doi.org/10.1007/978-3-031-61589-4_18]
  5. M. Brunetti, M.R.K. Mes, E. Lalla-Ruiz (2024). Smart Logistics Nodes: Concept and Classification. International Journal of Logistics Research and Applications. [https://doi.org/10.1080/13675567.2024.2327394]
  6. B. Gerrits, W. van Heeswijk, and M.R.K. Mes (2023). Towards self-organizing logistics in transportation: a literature review and typology. International Transactions in Operational Research. [https://doi.org/10.1111/itor.13408]
  7. R. van Steenbergen, W. Heeswijk, and M.R.K. Mes (2023). Reinforcement learning for humanitarian relief distribution with trucks and UAVs under travel time uncertainty. Transportation Research Part C. [https://doi.org/10.1016/j.trc.2023.104401]
  8. A.C. Morim, G. Campuzano, P. Amorim, M.R.K. Mes, and E. Lalla-Ruiz (2023). The Drone-Assisted Vehicle Routing Problem with Robot Stations. Expert Systems with Applications. [https://doi.org/10.1016/j.eswa.2023.121741]
  9. B. Gerrits, M.R.K. Mes, and R. Andringa (2023). A Simulation Model for Bio-Inspired Charging Strategies for Electric Vehicles in Industrial Areas. In Proceedings of the 2023 Winter Simulation Conference, edited by C.G. Corlu, S. Hunter, S. Onggo, H. Lam. Piscataway, New Jersey: IEEE.
  10. Koot, M., Mes M.R.K., and M.E. Iacob (2023) Building an Ontological Bridge Between Supply Chain Resilience and IoT Applications. In: D. Karastoyanova et al. (eds) EDOC 2023. Lecture Notes in Computer Science, vol 14367. Springer, Cham.
  11. K. Geevers, L. van Hezewijk, and M.R.K. Mes (2023). Multi-Echelon Inventory Optimization using Deep Reinforcement Learning. Central European Journal of Operations Research. [https://doi.org/10.1007/s10100-023-00872-2]
  12. R. Boschma, M.R.K. Mes, and L. de Vries (2023). Approximate Dynamic Programming for Container Stacking. European Journal of Operational Research. [https://doi.org/10.1016/j.ejor.2023.02.034]
  13. Pourmehdi, M., Iacob, M.E., Mes, M.R.K. (2023). Towards a Reference Architecture for Planning and Control Services. In: Griffo, C., Guerreiro, S., Iacob, M.E. (eds) Advances in Enterprise Engineering XVI. EEWC 2022. Lecture Notes in Business Information Processing, vol 473. Springer, Cham. [https://doi.org/10.1007/978-3-031-34175-5_8]
  14. Campuzano, G., E. Lalla-Ruiz, and M.R.K. Mes (2023). The Drone-Assisted Variable Speed Asymmetric Traveling Salesman Problem. Computers & Industrial Engineering. [https://doi.org/10.1016/j.cie.2023.109003]
  15. F. Akkerman, M.R.K. Mes, and E. Lalla-Ruiz (2022). Dynamic Time Slot Pricing Using Delivery Costs Approximations. In Computational Logistics – ICCL2022, Lecture Notes in Computer Science, edited by de Armas, J., Ramalhinho, H., Voß, S. (eds), pp. 214-230. Springer. [https://doi.org/10.1007/978-3-031-16579-5_15]
  16. Campuzano, G., Lalla-Ruiz, E., Mes, M. (2022). The Dynamic Drone Scheduling Delivery Problem. In Computational Logistics – ICCL2022, Lecture Notes in Computer Science, edited by de Armas, J., Ramalhinho, H., Voß, S. (eds), pp. 260-274. Springer. [https://doi.org/10.1007/978-3-031-16579-5_18]
  17. A. Asadi, S.N. Pinkley, and M.R.K. Mes (2022). A Markov Decision Process Approach for Managing Medical Drone Deliveries. Expert Systems with Applications 204, 117490. [https://doi.org/10.1016/j.eswa.2022.117490]
  18. F. Akkerman, M.R.K. Mes (2022). Distance Approximation to Support Customer Selection in Vehicle Routing Problems. Annals of Operations Research. [https://doi.org/10.1007/s10479-022-04674-8]
  19. A.E. Pérez Rivera, M.R.K. Mes (2022). Anticipatory Scheduling of Synchromodal Transport using Approximate Dynamic Programming. Annals of Operations Research. [https://doi.org/10.1007/s10479-022-04668-6]
  20. Gil A.F., Lalla-Ruiz E., Mes M., Castro C. (2021) Optimization of Green Pickup and Delivery Operations in Multi-depot Distribution Problems. In: Mes M., Lalla-Ruiz E., Voß S. (eds) Computational Logistics. ICCL 2021. Lecture Notes in Computer Science, vol 13004. Springer, Cham. [https://doi.org/10.1007/978-3-030-87672-2_32]
  21. Campuzano G., Lalla-Ruiz E., Mes M. (2021) A Multi-start VNS Algorithm for the TSP-D with Energy Constraints. In: Mes M., Lalla-Ruiz E., Voß S. (eds) Computational Logistics. ICCL 2021. Lecture Notes in Computer Science, vol 13004. Springer, Cham. [https://doi.org/10.1007/978-3-030-87672-2_26]
  22. C. Castiglione, D.M. Yazan, A. Alfieri, and M.R.K. Mes (2020). A Holistic Technological Eco-innovation Methodology for Industrial Symbiosis Development. Sustainable Production and Consumption. [https://doi.org/10.1016/j.spc.2021.09.002]
  23. M. Koot, M-E. Iacob, M.R.K. Mes (2021). A Reference Architecture for IoT-Enabled Dynamic Planning in Smart Logistics. 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, pp. 551-565. [https://doi.org/10.1007/978-3-030-79382-1_33]
  24. R. van Steenbergen, M. Brunetti, and M.R.K. Mes (2021). Network Generation for Simulation of Multimodal Logistics Systems. WSC2021.
  25. M. Koot, M.R.K. Mes, and M.E. Iacob (2020). A Systematic Literature Review of Supply Chain Decision Making supported by the Internet of Things and Big Data Analytics. Computers & Industrial Engineering 154, 107076. [https://doi.org/10.1016/j.cie.2020.107076]
  26. R. van Steenbergen and M.R.K. Mes (2020). Forecasting Demand Profiles of New Products. Decision Support Systems 139, 113401. [https://doi.org/10.1016/j.dss.2020.113401]
  27. M.R.K. Mes, I.M.H. Vliegen, and C.J.M. Doggen (2021). A quantitative analysis of integrated emergency posts. In Handbook of Healthcare Logistics - Bridging the Gap between Theory and Practice, edited by M.E. Zonderland, R.J. Boucherie, E.W. Hans, and N. Kortbeek. Springer International Series in Operations Research & Management Science, vol 302. [https://doi.org/10.1007/978-3-030-60212-3]
  28. E. Lalla-Ruiz and M.R.K. Mes (2021). Mathematical formulations and improvements for the multi-depot open vehicle routing problem. Optimization Letters 15, pp. 271–286. [http://link.springer.com/article/10.1007/s11590-020-01594-z]
  29. F. Akkerman and M.R.K. Mes (2020). Distance Approximation for Dynamic Waste Collection Planning. In Computational Logistics – ICCL2020, Lecture Notes in Computer Science, edited by  E.A. Lalla, M.R.K. Mes, and S. Voss, pp. 356-370. Springer. [https://doi.org/10.1007/978-3-030-59747-4_23]
  30. M.R.K. Mes and W. van Heeswijk (2020). Comparison of Manual and Automated Decision-Making with a Logistics Serious Game. In Computational Logistics – ICCL2020, Lecture Notes in Computer Science, edited by  E.A. Lalla, M.R.K. Mes, and S. Voss, pp. 698-714. Springer. [https://doi.org/10.1007/978-3-030-59747-4_45]
  31. T. van Benthem, M. Bergman, and M.R.K. Mes (2020). Solving a Bi-Objective Rich Vehicle Routing Problem with Customer Prioritization. In Computational Logistics – ICCL2020, Lecture Notes in Computer Science, edited by  E.A. Lalla, M.R.K. Mes, and S. Voss, pp. 183-199. Springer. [https://doi.org/10.1007/978-3-030-59747-4_12]
  32. M. Brunetti, M.R.K. Mes, and J. van Heuveln (2020). A Generic Simulation Framework for Smart Yards. In Proceedings of the 2020 Winter Simulation Conference, edited by K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, and R. Thiesing. Piscataway, New Jersey: IEEE.
  33. R. van Steenbergen and M.R.K. Mes (2020). A Simulation Framework for UAV-Aided Humanitarian Logistics. In Proceedings of the 2020 Winter Simulation Conference, edited by K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, and R. Thiesing. Piscataway, New Jersey: IEEE.
  34. B. Gerrits, M.R.K. Mes, and P.C. Schuur (2020). Mixing it up: Simulation of Mixed Traffic Container Terminals. In Proceedings of the 2020 Winter Simulation Conference, edited by K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, and R. Thiesing. Piscataway, New Jersey: IEEE.
  35. R. Bemthuis, M.R.K. Mes, M-E. Iacob, and P. Havinga (2020). Using Agent-based Simulation for Emergent Behavior Detection in Cyber-physical Systems. In Proceedings of the 2020 Winter Simulation Conference, edited by K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, and R. Thiesing. Piscataway, New Jersey: IEEE.
  36. I.O. Ryzhov, M.R.K. Mes, W.B. Powell, G.A. van den Berg (2019). Bayesian Exploration for Approximate Dynamic Programming. Operations Research 67(1), pp. 198-214. [https://doi.org/10.1287/opre.2018.1772]
  37. W.J.A. van Heeswijk, M.R.K. Mes, J.M.J. Schutten, and W.H.M. Zijm (2019). Evaluating Urban Logistics Schemes Using Agent-based Simulation. Transportation Science 54(3), pp. 651–675. [https://doi.org/10.1287/trsc.2019.0971]
  38. A.E. Pérez Rivera, M.R.K. Mes and J. van Hillegersberg (2019). A Simulation Game for Anticipatory Scheduling of Synchromodal Transportation, in: Hamada, R., Soranastaporn, S., Kanegae, H., Dumrongrojwatthana, P., Chaisanit, S., Rizzi, P., Dumblekar, V. (eds), Neo-Simulation and Gaming Toward Active Learning, Springer Translational Systems Sciences 18.
  39. Bemthuis, R.H., Koot, M., Mes, M.R.K., Bukhsh, F.A., Iacob, M.-E, & Meratnia, N (2019). An agent-based process mining architecture for emergent behavior analysis. In 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE, in press.
  40. M.R.K. Mes and M. Koot (2019). Simulation Solution Validation for an Integrated Emergency Post. In Proceedings of the 2019 Winter Simulation Conference, edited by N. Mustafee, M. Rabe, K.-H.G. Bae, C. Szabo, S. Lazarova-Molnar. Piscataway, New Jersey: IEEE.
  41. B. Gerrits, M.R.K. Mes and P. Schuur (2019). Simulation of Real-Time and Opportunistic Truck Platooning at the Port of Rotterdam. In Proceedings of the 2019 Winter Simulation Conference, edited by N. Mustafee, M. Rabe, K.-H.G. Bae, C. Szabo, S. Lazarova-Molnar. Piscataway, New Jersey: IEEE.
  42. A.E. Pérez Rivera, M.R.K. Mes (2019). Integrated scheduling of drayage and long-haul operations in synchromodal transport. Flexible Services and Manufacturing 31, pp. 763–806. [https://doi.org/10.1007/s10696-019-09336-9]
  43. W. Chen, M.R.K. Mes, J.M.J. Schutten, and J. Quint (2019). A ride-sharing problem with meeting points and return restrictions. Transportation Science 53(2), pp. 319-622. [https://doi.org/10.1287/trsc.2018.0832]
  44. I.A. Bikker, Martijn Mes, Antoine Sauré, and Richard J. Boucherie (2018). Online capacity planning for rehabilitation treatments: an approximate dynamic programming approach. Probability in the Engineering and Informational Sciences 34(3), pp. 381-405. [https://doi.org/10.1017/S0269964818000402]
  45. B. Gerrits, M.R.K. Mes, P.C. Schuur (2018). A Simulation Model for the Planning and Control of AGVs at Automated Container Terminals. In Proceedings of the 2018 Winter Simulation Conference, edited by M. Rabe, A. Skoogh, N. Mustafee, and A.A. Juan. Piscataway, New Jersey: IEEE.
  46. D.M. Yazan, D. Cafagna, M.R.K. Mes, L. Fraccascia, P. Ponfrandolfo, and H. Zijm (2018). Economic sustainability of biogas production from animal manure: A regional circular economy model. Management Research Review 41(5), pp. 605-624. [https://doi.org/10.1108/MRR-02-2018-0053]
  47. D.M. Yazan, L. Fraccascia, M.R.K. Mes, H. Zijm (2018). Cooperation in manure-based biogas production networks: An agent-based modelling approach. Applied Energy 212, pp. 820-833. [https://doi.org/10.1016/j.apenergy.2017.12.074]
  48. B. Gerrits, M.R.K. Mes, P.C. Schuur (2017). An Agent-Based Simulation Model For Autonomous Trailer Docking. In Proceedings of the 2017 Winter Simulation Conference, edited by V. Chan, A. D’Ambrogio, G. Zacharewicz, and N. Mustafee. Piscataway, New Jersey: IEEE.
  49. A.E. Pérez Rivera, M.R.K. Mes (2017). Scheduling Drayage Operations in Synchromodal Transport. In T. Bektas et al. (Eds.), Computational Logistics – ICCL 2017, Lecture Notes in Computer Science, pp. 404-419. Springer. [https://doi.org/10.1007/978-3-319-68496-3_27]
  50. W.J.A. van Heeswijk, M.R.K. Mes, and J.M.J. Schutten (2017). The delivery dispatching problem with time windows for urban consolidation centers. Transportation Science 53(1), pp. 203–22. [https://doi.org/10.1287/trsc.2017.0773]
  51. M.R.K. Mes, A.E. Pérez Rivera (2017). Approximate Dynamic Programming by Practical Examples. In: Richard Boucherie & Nico M. van Dijk (Eds.), Markov Decision Processes in Practice. International Series in Operations Research & Management Science (248). Springer. ISBN 9783319477664.
  52. W. Chen, M.R.K. Mes, and J.M.J. Schutten (2016), Multi-hop driver-parcel matching problem with time windows. Flexible Services and Manufacturing Journal 30, pp. 517–553. [https://doi.org/10.1007/s10696-016-9273-3]
  53. W.J.A. van Heeswijk, M.R.K. Mes, J.M.J. Schutten, and W.H.M. Zijm (2016). Freight consolidation in intermodal networks with reloads. Flexible Services and Manufacturing Journal 30, pp. 452–485. [https://doi.org/10.1007/s10696-016-9259-1]
  54. A.E. Pérez Rivera, M.R.K. Mes (2016). Anticipatory Freight Selection in Intermodal Long-haul Round-trips. Transportation Research Part E: Logistics and Transportation Review 105, pp. 176-194. [https://doi.org/10.1016/j.tre.2016.09.002]
  55. M.R.K. Mes and A.M. Douma (2016). Agent-Based Support for Container Terminals to make Appointments with Barges. In Paias, A., Ruthmair, M., and Voβ, S. (Eds.), Computational Logistics – ICCL 2016, Lecture Notes in Computer Science, pp. 80-95. Springer. [https://doi.org/10.1007/978-3-319-44896-1_6]
  56. W.J.A. van Heeswijk, M.R.K. Mes, and M. Schutten (2016). An Agent-Based Simulation Framework to evaluate Urban Logistics Schemes. In Paias, A., Ruthmair, M., and Voβ, S. (Eds.), Computational Logistics – ICCL 2016, Lecture Notes in Computer Science, pp. 369-383. Springer. [https://doi.org/10.1007/978-3-319-44896-1_24]
  57. A.E. Pérez Rivera, M.R.K. Mes (2016). Service and Transfer Selection for Freights in a Synchromodal Network. In Paias, A., Ruthmair, M., and Voβ, S. (Eds.), Computational Logistics – ICCL 2016, Lecture Notes in Computer Science, pp. 227-242. Springer. [https://doi.org/10.1007/978-3-319-44896-1_15]
  58. D.M. Yazan, I. van Duren, M.R.K. Mes, S. Kersten, J. Clancy, H. Zijm (2016). Design of sustainable second-generation biomass supply chains. Biomass and Bioenergy 94, pp. 173-186. [https://doi.org/10.1016/j.biombioe.2016.08.004]
  59. N. Borgman, M.R.K. Mes, I.M.H. Vliegen, and E.W. Hans (2016). Improving the Design and Operation of an Integrated Emergency Post using Simulation. In Mustafee, Navonil (Ed), Operational Research for Emergency Planning in Healthcare 1, pp. 164–189.
  60. P.J.H. Hulshof, M.R.K. Mes, R.J. Boucherie, E.W. Hans (2016). Patient admission planning using Approximate Dynamic Programming. Flexible Services and Manufacturing 28(1): pp. 30-61. [https://doi.org/10.1007/s10696-015-9219-1]
  61. W. van Heeswijk, M.R.K. Mes, and M. Schutten (2015). An Approximate Dynamic Programming Approach to Urban Freight Distribution with Batch Arrivals. In Corman, F., Voβ, S., Negenborn, R.R. (Eds.), Computational Logistics – ICCL 2015, Lecture Notes in Computer Science, pp. 61-75. Springer. [https://doi.org/10.1007/978-3-319-24264-4_5]
  62. A.E. Pérez Rivera, M.R.K. Mes (2015). Dynamic Multi-period Freight Consolidation. In Corman, F., Voβ, S., Negenborn, R.R. (Eds.), Computational Logistics – ICCL 2015, Lecture Notes in Computer Science, pp. 370-385. Springer. [https://doi.org/10.1007/978-3-319-24264-4_26]
  63. M.R.K. Mes, M.-E. Iacob (2015). Synchromodal Transport Planning at a Logistics Service Provider. In Zijm, H., Klumpp, M., Clausen, U., Hompel, M.t. (Eds.), Logistics and Supply Chain Innovation - Bridging the Gap between Theory and Practice, Lecture Notes in Logistics, pp. 23–36. Springer Berlin Heidelberg.
  64. A. Dobrkovic, M.-E. Iacob, J. van Hillegersberg, M.R.K. Mes, and M. Glandrup (2015). Towards an Approach for Long Term AIS-Based Prediction of Vessel Arrival Times. In Zijm, H., Klumpp, M., Clausen, U., Hompel, M.t. (Eds.), Logistics and Supply Chain Innovation - Bridging the Gap between Theory and Practice, Lecture Notes in Logistics, pp. 281–294. Springer Berlin Heidelberg.
  65. R. van der Kooij, M.R.K. Mes, E.W. Hans (2014). Simulation Framework to Analyse Operating Room Release Mechanisms. In Proceedings of the 2014 Winter Simulation Conference, edited by A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller. Piscataway, New Jersey: IEEE.
  66. T. van Dijk, M.R.K. Mes, J.M.J. Schutten, J. Gromicho (2014). A Unified Race Algorithm for Offline Parameter Tuning. In Proceedings of the 2014 Winter Simulation Conference, edited by A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller. Piscataway, New Jersey: IEEE.
  67. M.R.K. Mes, J.M.J. Schutten, A.E. Pérez Rivera (2014). Inventory routing for dynamic waste collection. Waste Management 34(9), pp. 1564–1576. [https://doi.org/10.1016/j.wasman.2014.05.011]
  68. N. Borgman, M.R.K. Mes, I.M.H. Vliegen, and E.W. Hans (2015). Improving the Design and Operation of an Integrated Emergency Post using Simulation. Journal of Simulation 9(2): 99-110. [https://doi.org/10.1057/jos.2014.5]
  69. R. van Urk, M.R.K. Mes, and E.W. Hans (2013). Anticipatory Routing of Police Helicopters. Expert Systems with Applications 40(17), pp. 6938–6947. [https://doi.org/10.1016/j.eswa.2013.06.044]
  70. M.R.K. Mes, M.-E. Iacob, and J. van Hillegersberg (2013). A Distributed Barge Planning Game, In: S.A. Meijer, R. Smeds (eds), Frontiers in Gaming Simulation, Springer Lecture Notes in Computer Science, Vol. 8264, p 214-221.
  71. M.R.K. Mes, M.C. van der Heijden, and P.C. Schuur (2013). Interaction between intelligent agent strategies for real-time transportation planning. Central European Journal of Operations Research 21(2), pp. 337-358. [https://doi.org/10.1007/s10100-011-0230-7]
  72. M.R.K. Mes and M. Bruens (2012). Simulation Modelling of an Integrated Emergency Post. In Proceedings of the 2012 Winter Simulation Conference, edited by C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A. M. Uhrmacher. Piscataway, New Jersey: IEEE.
  73. M.R.K. Mes, W.B. Powell, and P.I. Frazier (2011). Hierarchical Knowledge-Gradient for Sequential Sampling. Journal of Machine Learning Research 12(Oct), pp. 2931−2974.
  74. M.R.K. Mes, M.C. van der Heijden, and P.C. Schuur (2010). Look-ahead strategies for dynamic pickup and delivery problems. OR Spectrum 32(2), pp. 395-421. [https://doi.org/10.1007/s00291-008-0146-3]
  75. M.R.K. Mes, M.C. van der Heijden, and P.C. Schuur (2009). Dynamic threshold policy for delaying and breaking commitments in transportation auctions. Transportation Research Part C 17(2), pp. 208-223. [https://doi.org/10.1016/j.trc.2008.03.001]
  76. M.R.K. Mes, M.C. van der Heijden, and Jos van Hillegersberg (2008). Design choices for agent-based control of AGVs in the dough making process. Decision Support Systems 44(4), pp. 983-999. [https://doi.org/10.1016/j.dss.2007.11.005]
  77. M.R.K. Mes, M.C. van der Heijden, and A. van Harten (2007). Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems. European Journal of Operational Research 181(1), pp. 59–75. [https://doi.org/10.1016/j.ejor.2006.02.051]

BOOKS / Book chapters / extended abstracts / proceedings:

  1. M.R.K. Mes, W.J.A. van Heeswijk, and F.R. Akkerman (2022). Reinforcement Learning for Data-Driven Logistics. Extended abstract for the Route 2022 workshop.
  2. M.R.K. Mes, E.A. Lalla, and S. Voß (2021). Editors of the book Computational Logistics, connected to the 12th International Conference on Computational Logistics. Part of the Lecture Notes in Computer Science book series, Springer, Cham. [https://doi.org/10.1007/978-3-030-87672-2]
  3. F. Akkerman, E.A. Lalla-Ruiz, and M.R.K. Mes (2021). Cross-Docking: Current Research versus Industry Practice and Industry 4.0 Adoption. In T. Bondarouk and M. Olivas-Lujan (Eds.),  Advanced Series in Management, Emerald Publishing. [https://doi.org/10.1108/S1877-636120220000028007]
  4. E.A. Lalla, M.R.K. Mes, and S. Voß (2020). Computational Logistics – Online, ICCL2020, The Netherlands. IFORS News 15(4), pp. 34-35. [https://www.ifors.org/newsletter/ifors-news-dec2020.pdf]
  5. E.A. Lalla, M.R.K. Mes, and S. Voß (2020). Editors of the book Computational Logistics, connected to the 11th International Conference on Computational Logistics. Part of the Lecture Notes in Computer Science book series, Springer, Cham. [https://doi.org/10.1007/978-3-030-59747-4]
  6. O.A.L. Eikenbroek, M.R.K. Mes, and E.C. van Berkum (2019). Online route planning in response to non-recurrent traffic disturbances. Presented at 30th European Conference on Operational Research, EURO 2019, Dublin, Ireland.
  7. O.A.L. Eikenbroek, M.R.K. Mes, and E.C. van Berkum (2019). Pattern Recognition in Urban Traffic Flows. Paper presented at 98th Transportation Research Board (TRB) Annual Meeting 2019, Washington, United States.
  8. A.E. Pérez Rivera, M.R.K. Mes and J. van Hillegersberg (2018). A Simulation Game for Anticipatory Scheduling of Synchromodal Transportation. ISAGA 2018 Conference Proceedings, Thailand.
  9. A.E. Pérez Rivera and M.R.K. Mes (2018). Integrated Scheduling of Drayage and Long-haul Transportation in Synchromodality. Odysseus Workshop 2018, Cagliari, Italy.
  10. M.R.K. Mes and B. Gerrits (2018). Multi-agent Systems. In Zijm, H., Klumpp, M., Regattieri, A.,Heragu, S. (Eds.), Operations, Logistics and Supply Chain Management. Springer Berlin Heidelberg.
  11. W. van Heeswijk, M.R.K. Mes and J.M.J. Schutten (2018). Transportation Management. In Zijm, H., Klumpp, M., Regattieri, A.,Heragu, S. (Eds.), Operations, Logistics and Supply Chain Management. Springer Berlin Heidelberg. [http://dx.doi.org/10.1007/978-3-319-92447-2_21]
  12. A.E. Pérez Rivera, M.R.K. Mes (2017). Integrated scheduling in synchromodal transport. LOGMS 2017 Conference Proceedings, Bergen, Norway.
  13. A.E. Pérez Rivera, M.R.K. Mes (2017). Scheduling synchromodal freight transport using approximate dynamic programming. VeRoLog 2017 Conference Proceedings, Amsterdam, The Netherlands.
  14. M.R.K. Mes (2017). Simulation Modelling using Practical Examples: A Plant Simulation Tutorial. University of Twente, Enschede, The Netherlands.
  15. M.R.K. Mes and J.M.J. Schutten (2016). Dynamische afvalinzameling; efficiënter en slimmer. STAtOR 17(3), pp. 18-21.
  16. A.E. Pérez Rivera, M.R.K. Mes (2016). Pre- and end-haulage operations in a multi-depot and multi-resource synchromodal network. TRISTAN 2016, Aruba.
  17. W. Chen, M.R.K. Mes, and J.M.J. Schutten (2016). A ride-sharing problem with meeting points and return restriction. TRISTAN 2016, Aruba.
  18. W. van Heeswijk, M.R.K. Mes, and M. Schutten (2016). An Agent-Based Simulation Study on the Effectiveness of Urban Consolidation Initiatives. TRISTAN 2016, Aruba.
  19. D.M. Yazan, L. Fraccascia, M.R.K. Mes, and W.H.M. Zijm (2016). Cooperation in manure-based biogas production networks: An agent-based modelling approach. In: ILS 2016, Information Systems, Logistics and Supply Chain Conference, 01-06-2016 - 04-06-2016, Bordeaux.
  20. A.E. Pérez Rivera, M.R.K. Mes (2015). Dynamic freight selection for reducing long-haul round trip costs. VeRoLog 2015, Vienna, Austria.
  21. W. van Heeswijk, M.R.K. Mes, and M. Schutten (2015). An ADP approach towards the delivery dispatching problem with time windows. TSL Workshop, Berlin 8-7-2015.
  22. D.M. Yazan, D. Cafagna, M.R.K. Mes, L. Fraccascia, P. Ponfrandolfo, and H. Zijm (2015). Economic sustainability of biogas production from animal manure: A regional circular economy model. In: Circular Economy Inspiring Sustainable Innovation, The 4th GIN symposium, Mexico City.
  23. M. Schutten, W. van Heeswijk, and M.R.K. Mes (2014). Consolidation planning in transportation networks with transhipments. VeRoLog 2014, Oslo, Norway.
  24. R. van Urk, and M.R.K. Mes (2014). Optimized Time Differentiated Parcel Delivery using Private and Public Transport. VeRoLog 2014, Oslo, Norway.
  25. D.M. Yazan, I. van Duren, M.R.K. Mes, S. Kersten, J. Clancy, and H. Zijm (2013). A comparative supply chain sustainability evaluation of mobile pyrolysis plants and pyrolysis-based bio-refineries. International Symposium on Biorefinery for Food, Fuel and Materials (BFF2013), Wageningen, the Netherlands, April 7-10.
  26. M.R.K. Mes, and R. van Urk (2012). Synchromodal Transport Planning. VeRoLog 2013, Southampton, UK.
  27. M.R.K. Mes (2012). Using Simulation to Assess the Opportunities of Dynamic Waste Collection. In Use Cases of Discrete Event Simulation, S. Bangsow (Eds). Springer, pp. 277-307.
  28. M.R.K. Mes, I.M.H. Vliegen, R. Visser (2012). A Simulation Study of an Integrated Emergency Post. ORAHS 2012 Conference Proceedings, Enschede, The Netherlands.
  29. M.R.K. Mes (2008). Sequential Auctions for Full Truckload Allocation. PhD thesis, University of Twente.
  30. M.R.K. Mes, M.C. van der Heijden, and P.C. Schuur (2009). Dynamic threshold policy for delaying and breaking commitments in transportation auctions. TRISTAN VI, Phuket Island, Thailand.
  31. M.R.K. Mes, M.C. van der Heijden, and P.C. Schuur (2006). Opportunity costs calculation in agent-based vehicle routing and scheduling. Odysseus Workshop 2006, Altea, Spain.

Interviews and articles in the Dutch press:

  1. Tubantia, 28 May 2020, Zo wordt in Twente gewerkt aan ’s wereld eerste onbemande hulpvliegtuig. https://www.tubantia.nl/enschede/zo-wordt-in-twente-gewerkt-aan-s-wereld-eerste-onbemande-hulpvliegtuig~af367536/
  2. RTV Oost, 27 May 2020, Nieuw onbemand hulpverleningsvliegtuig wordt getest op Twente Airport. https://www.rtvoost.nl/nieuws/331011/Nieuw-onbemand-hulpverleningsvliegtuig-wordt-getest-op-Twente-Airport. Also available on: https://www.pilootenvliegtuig.nl/2020/05/27/wings-for-aid-test-op-twente-airport/
  3. The future is self-organizing. Special issue of the Hightech Business and Entrepreneurship department, a publication by U-Today, January 2020. [https://www.utoday.nl/uploads/magazines/HBE%20Special.pdf]
  4. Uitstoot in steden kan tot 70% omlaag. Press release related to the PhD defence of Wouter van Heeswijk. Several newspaper reports have appeared, e.g., on fluxenergie.nl, binnenlandsbestuur.nl, and blikopnieuws.nl.
  5. Modellen voor nieuwe vormen van pakket- en personenvervoer, 23 april 2017, CargoHitching Magazine: waar pakketjes en personen samengaan.
  6. Nieuwsuur, 21 september 2015, Interview met Karine van Hal over rekenmodellen voor informatie gestuurde luchtsteun (reportage van 9 minute).
  7. Nieuwsuur.nl, 21 september 2015, Meer arrestaties door politieheli's dankzij patronen criminelen, http://nos.nl/nieuwsuur/artikel/2058913-meer-arrestaties-door-politieheli-s-dankzij-patronen-criminelen.html
  8. Forse winst voor Twente Milieu, Tubantia, 2 juli 2013 [dynamische afvalinzameling op basis van sensorinformatie].
  9. Politie zet heli's efficiënter in, Het Parool, 29 juni 2013.
  10. De politie surveilleert steeds vaker vanuit de lucht. Hamvraag is hoe dure vlieguren effectief te maken, NRC Handelsblad, 11 april 2013.
  11. Meer blauw in de lucht, NRC Next, 9 april 2013.
  12. Politiehelikopters surveilleren daar waar al eens iets gebeurde, website NRC (http://www.nrc.nl/nieuws/2013/04/09/meer-blauw-in-de-lucht-politiehelikopters-op-basis-van-misdaadgegevens/), 9 April 2013.
  13. Pakkans criminelen stijgt aanzienlijk, website University of Twente (http://www.utwente.nl/archief/2013/04/pakkans_criminelen_stijgt_aanzienlijk.docx/), 9 April 2013.
  14. Statistiek bepaalt route politieheli, Nederlands Dagblad, 9 April 2013.
  15. Televisie interview met Rick van Urk over een computerprogramma voor bepaling van vliegroutes voor de politiehelikopters, Hart van Nederland, 9 April 2013.
  16. Radio interview met Martijn Mes over een computerprogramma voor bepaling van vliegroutes voor de politiehelikopters, Enschede FM, 9 April 2013.
  17. Radio interview met Rick van Urk over een computerprogramma voor bepaling van vliegroutes voor de politiehelikopters, RTV Oost, 9 April 2013.
  18. Intelligencegestuurde luchtsteun, vliegen op hoog niveau, website Politie (http://www.politie.nl/nieuws/2013/april/8/11-locatiebepaling.html), 9 april 2013.
  19. Efficiënt aanmeren in Rotterdamse Haven, 5 april 2013, ScienceGuide.
  20. Innovatief plansysteem voor Rotterdamse haven, website Universiteit Twente (http://www.utwente.nl/archief/2013/04/innovatief_plansysteem_voor_rotterdamse_haven.docx/), 3 april 2013.
  21. Spoedpost meer gebaat bij extra huisarts of verpleegkundige?, website Universiteit Twente (http://www.utwente.nl/archief/2013/03/spoedpost_meer_gebaat_bij_extra_huisarts_of_verpleegkundige.doc/), 28 maart 2013.
  22. ‘The Sims’ in de huisartsenpost, Tubantia, December 2012.
  23. Spoedpost Almelo landelijk voorbeeld, Tubantia, November 2012.
  24. Spoedpost overleeft kinderziektes, Tubantia, Mei 2011 & 112 Netwerk, juni 2011.
  25. UT onderzoekt de Almelose Spoedpost, Tubantia, 24 mei 2011.
  26. BATMAN maakt Rotterdamse haven slimmer, diverse publicaties (http://www.utwente.nl/archief/2011/09/batman_maakt_rotterdamse_haven_slimmer.docx/), september 2011.
  27. Motion in meel. Interview in Aandrijven & Besturen, No. 10, October 22, 2008.
  28. Coping with uncertainty in transport planning. Interview in CTIT progress report 2007-2008.
  29. Tricky dat alle kennis in het hoofd van de planner zit. Interview in Nieuwsblad Transport, No. 14, April 2, 2008.
  30. Minder vrachtwagens leeg onderweg dankzij 'agents' met vooruitziende blik. Press release about my PhD research. Several newspaper reports have appeared. For example in Logistiek.nl (March 28, 2008), Automatisering Gids (March 27, 2008), Nieuwsblad Transport (March 27, 2008) and many others.
  31. Virtuele agents verhogen beladingsgraad, 26 maart 2008, TTM.
  32. Beter dan traditionele routeplanner. Interview with A. van Harten and M.R.K. Mes in IT Logistiek, No. 6, June 1, 2004.

Selection of presentations

Conference presentations at the INFORMS Annual Meetings:

Selection of invited talks:

demonstration of simulation models & simulation tutorial

A selection of some of my simulation models can be found below. These models were implemented in Tecnomatix Plant Simulation from Siemens. For this simulation software, I wrote an extensive tutorial that is currently used by various educational institutions.



Integrated Emergency Post [view]
Simulation of an Integrated Emergency Post (Emergency Department and General Practitioner Post).



Waste Collection [view]
Simulation of Waste Collection from Underground Containers (Inventory Routing Problem).



Industrial Bakery [view]
Simulation of Automated Guided Vehicles used in the Dough Making Process in an Industrial Bakery.



Underground Logistic System [view]
Simulation of an Underground Logistic System aimed to be built at Amsterdam Airport Schiphol.

Simulation Modelling using Practical Examples: A Plant Simulation Tutorial

This tutorial consists of two parts. The first part is primarily designed for a bachelor module, where you will build a number of basic models in Plant Simulation. Each of these chapters end with a working simulation model and an assignment. The simulation models presented in these chapters revolve around one running example: the modelling and optimisation of a General Practitioner’s office. The second part is primarily designed for a master course, where you will build more advanced and more graphically oriented simulation models. Again, each of these chapters contain an assignment. However, we use another running example throughout these chapters, namely of a car manufacturer.

[download tutorial including accompanying files]  

Teaching

Master lectures:

Bachelor lectures:

Keywords

Transportation, green logistics, multi-agent systems, auctions, freight transport, dynamic vehicle routing problems, stochastic optimization, artificial intelligence, optimal learning, machine learning, reinforcement learning, planning, scheduling, logistics, simulation.

Publication archive

Full electronic versions of my publications can be retrieved from UTpublications.

PhD thesis and defence (2008)