Ravelijn

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

Universitair docent
BMS-HBE-IEMS
Ravelijn 3351
w.j.a.vanheeswijk@utwente.nl
+31534898460
Visitekaartje

Expertises

  • Computer Science

    • Reinforcement Learning
    • Dynamic Programming
    • Function Approximation

  • Social Sciences

    • Motor Vehicles
    • Transport
    • Learning System
    • Machine Learning
    • Stochastics

Organisaties

Publicaties

2026

Progressive lower bound evaluation for urban road renovation scheduling (2026)Computer-aided civil and infrastructure engineering, 51. Article 100174 (E-pub ahead of print/First online). Bosch, R., Rogetzer, P., van Heeswijk, W. & Mes, M.https://doi.org/10.1016/j.cacaie.2026.100174Anatomy of peer-to-peer (P2P) lending fraud: A review with managerial implications (2026)International Journal of Information Management Data Insights, 6(2). Article 100425 (E-pub ahead of print/First online). Machado, M. R., Coita, I. F., Gomez, L., Wenzlaff, K., van Heeswijk, W., Bernard, F. S., Pop, M. V. & Osterrieder, J.https://doi.org/10.1016/j.jjimei.2026.100425An agent-based model of rumor-induced volatility in financial markets (2026)Journal of Behavioral and Experimental Finance, 49. Article 101135. Marisetty, V. B., van Heeswijk, W. & Narayanan, A.https://doi.org/10.1016/j.jbef.2025.101135Sustainability-Related Risks in Credit Risk Modeling: Evidence, Limitations, and the Role of Machine Learning (2026)[Working paper › Preprint]. Social Science Research Network (SSRN) (Submitted). Massei, M., van Heeswijk, W., Huang, X. & Spierdijk, L.https://doi.org/10.2139/ssrn.6292484Efficient 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.2602.15554Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete and Hybrid Action Spaces (2026)[Working paper › Preprint]. ArXiv.org. Hoppe, H., Akkerman, F., van Heeswijk, W. & Schiffer, M.https://doi.org/10.48550/arXiv.2602.08616Sustainability-Related Risks in Credit Risk Modeling: Evidence, Limitations, and the Role of Machine Learning (2026)[Working paper › Preprint]. Social Science Research Network (SSRN) (Submitted). Massei, M., van Heeswijk, W., Huang, X. & Spierdijk, L.https://doi.org/10.2139/ssrn.6046795Differentiated Pickup Point Offering for Emission Reduction in Last-Mile Delivery (2026)[Working paper › Preprint]. ArXiv.org. Galiullina, A., van Heeswijk, W. J. A. & van Woensel, T.https://doi.org/10.48550/arXiv.2601.14196

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.2512.11187Strategic bidding in freight transport using deep reinforcement learning (2025)Annals of operations research, 350(1), 131-168. van Heeswijk, W. J. A.https://doi.org/10.1007/s10479-022-04572-z

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