| Position: | HGL |
| Room: | Neuron 1.106 |
| Tel (internal): | |
| Links: | Scopus page TU/e page |
Recent courses
Recent presentations
Recent projects
- Dynamic and Interactive Determination of the Right Supply Chain Optimization Problem - Staff
- Learning and Explaining Optimization - Staff
- Explainable Supply Chain Optimization - Staff
Recent publications
- Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems - Lo Bianco, R., Dijkman, R. M., Nuijten, W. P. M., & van Jaarsveld, W. L. (2023). Action-Evolution Petri Nets: a Framework for Modeling and Solving Dynamic Task Assignment Problems. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Read More ...
- Analytical Problem Solving Based on Causal, Correlational and Deductive Models - de Mast, J., Steiner, S., Nuijten, W. P. M., & Kapitan, D. (2023). Analytical Problem Solving Based on Causal, Correlational and Deductive Models. American Statistician, 77(1), 51-61. https://doi.org/10.1080/00031305.2021.2023633 Abstract Many approaches for solving problems in business and industry are based on analytics and statistical modeling. Analytical problem solving is driven by the modeling of relationships Read More ...
- Scheduling a Real-World Photolithography Area with Constraint Programming - Deenen, P. C., Nuijten, W. P. M., & Akcay, A. (2023). Scheduling a Real-World Photolithography Area with Constraint Programming. IEEE Transactions on Semiconductor Manufacturing, 36(4), 590-598. Article 10214506. https://doi.org/10.1109/TSM.2023.3304517 Abstract This paper studies the problem of scheduling machines in the photolithography area of a semiconductor manufacturing facility. The scheduling problem is characterized as an unrelated Read More ...
- Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts - Reijnen, R., Zhang, Y., Nuijten, W. P. M., Senaras, C., & Goldak, M. (2021). Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI 2020) (pp. 2647-2654). Article 9308584 IEEE Press. https://doi.org/10.1109/SSCI47803.2020.9308584 Abstract A multi-agent path finding (MAPF) problem is concerned Read More ...
- Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction - Karetnikov, A., Nuijten, W., & Hassani, M. (2021). Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction. In P. Pezarat-Correia, J. Vilas-Boas, & J. Cabri (Eds.), icSPORTS 2021 – Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support (pp. 43-53). SciTePress Digital Library. Abstract In individual sports, the judgment Read More ...
- Publications in 2017 - Article Scientific peer reviewed Arriagada-Benítez, M., Sepúlveda, M., Munoz-Gama, J. & Buijs, J.C.A.M. (2017). Strategies to automatically derive a process model from a configurable process model based on event data. Applied Sciences, 7(10):1023. Bolt, A., de Leoni, M. & van der Aalst, W.M.P. (2017). Process variant comparison: using event logs to detect differences in behavior Read More ...
- Publications in 2016 - Article Scientific peer reviewed Van Der Aa, Han, Leopold, H. & Reijers, H.A. (2016). Dealing with behavioral ambiguity in textual process descriptions. Lecture notes in computer science, 9850, 271-288. Scopus. van der Aa, J.H., Reijers, H.A. & Vanderfeesten, I.T.P. (2016). Designing like a pro : the automated composition of workflow activities. Computers in Industry, 75, Read More ...