dr.ir. W.J.A. van Heeswijk (Wouter)

Engineering & Materials Science

# Autonomous Agents
# Consolidation
# Dynamic Programming
# Logistics
# Supply Chains

Business & Economics

# Consolidation

Mathematics

# Reinforcement Learning
# Serious Games

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

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

Akkerman, F., Luy, J. , Heeswijk, W. V., & Schiffer, M. (2023). Handling Large Discrete Action Spaces via Dynamic Neighborhood Construction. ArXiv.org. https://arxiv.org/abs/2305.19891

Piest, J. P. S., Slavova, S. , & van Heeswijk, W. J. A. (2023). A Reference Use Case, Data Space Architecture, and Prototype for Smart Truck Parking. In Proceedings of the 22nd CIAO! Doctoral Consortium, and Enterprise Engineering Working Conference Forum 2022 co-located with 12th Enterprise Engineering Working Conference (EEWC 2022) (pp. 1-15). Article 1 (CEUR Workshop Proceedings; Vol. 3388). CEUR. https://ceur-ws.org/Vol-3388/paper1.pdf

van Heeswijk, W. J. A. (2022). Strategic bidding in freight transport using deep reinforcement learning. Annals of operations research. Advance online publication. https://doi.org/10.1007/s10479-022-04572-z

Slavova, S. , Piest, J. P. S. , & van Heeswijk, W. J. A. (2022). Predicting truck parking occupancy using machine learning. Procedia computer science, 201, 40-47. https://doi.org/10.1016/j.procs.2022.03.008

van Heeswijk, W., & La Poutre, H. (2021). Deep reinforcement learning in linear discrete action spaces. In K-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, & R. Thiesing (Eds.), Proceedings of the 2020 Winter Simulation Conference, WSC 2020 (pp. 1063-1074). Article 9384078 (Proceedings - Winter Simulation Conference; Vol. 2020). IEEE. https://doi.org/10.1109/WSC48552.2020.9384078

Mes, M. , & van Heeswijk, W. (2020). Comparison of Manual and Automated Decision-Making with a Logistics Serious Game. In E. Lalla-Ruiz, M. Mes, & S. Voß (Eds.), Computational Logistics - 11th International Conference, ICCL 2020, Proceedings (pp. 698-714). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12433 LNCS). Springer. https://doi.org/10.1007/978-3-030-59747-4_45

van Heeswijk, W. (2020). Smart Containers with Bidding Capacity: A Policy Gradient Algorithm for Semi-Cooperative Learning. In E. Lalla-Ruiz, M. Mes, & S. Voß (Eds.), Computational Logistics: 11th International Conference, ICCL 2020, Enschede, The Netherlands, September 28–30, 2020, Proceedings (pp. 52-67). (Lecture notes in computer science; Vol. 12433). Springer. https://doi.org/10.1007/978-3-030-59747-4_4

Bekijk alle publicaties van deze medewerker

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.