Hi, I am Collin Drent.
I am an Assistant Professor in the School of Industrial Engineering of Eindhoven University of Technology. My research centers around solving challenging data-driven decision problems that have practical relevance using operations research techniques. Specifically, I study the integration of learning and optimization to address operational challenges that decision makers face in practice.
Prior to joining the School of Industrial Engineering, I obtained my PhD in Applied Mathematics from the Department of Mathematics and Computer Science of Eindhoven University of Technology.
I am always open to new collaborations. You can reach me at: c.drent at tue dot nl
Research
Publications
Drent, C., Drent, M., van Houtum, G.J. (2023). Optimal data pooling for shared learning in maintenance operations. Forthcoming at Operations Research Letters.
Drent, C., Drent, M., Arts, J.J., Kapodistria, S. (2023). Real-time integrated learning and decision making for cumulative shock degradation. Manufacturing & Service Operations Management, 25(1), 235–253.
The degradation data set of the corresponding case study can be downloaded here.
Drent, C., Kapodistria, S., Boxma, O. (2020). Censored life-time learning: Optimal Bayesian age-replacement policies. Operations Research Letters, 48(6), 827–834.
Drent, C., Olde Keizer, M., van Houtum, G.J. (2020). Dynamic dispatching and repositioning policies for fast-response service networks. European Journal of Operational Research, 285(2), 583–598.
Drent, C., Kapodistria, S., Resing, J.A.C. (2019). Condition-based maintenance policies under imperfect maintenance at scheduled and unscheduled opportunities. Queueing Systems, 93(3-4), 269–308.
Working papers
Condition-based production for stochastically deteriorating systems: Optimal policies and learning, with Joachim Arts and Melvin Drent. Minor Revision at Manufacturing & Service Operations Management.
Bayesian process control for critical systems, with Stella Kapodistria. Major Revision at Production and Operations Management.
Dedicated maintenance and repair shop control for spare parts networks, with Chaaben Kouki, Melvin Drent, and Mohamed-Zied Babai. Submitted.
Theses
Drent, C. (2022). Structured learning and decision making for maintenance. PhD thesis, Eindhoven University of Technology.
Media coverage: TechXplore, TU/e, De Ingenieur (in Dutch), Industrial Maintenance (in Dutch).
Winner of Willem R. van Zwet Award (best Dutch PhD thesis in statistics or operations research in 2022; see VVSOR and TU/e)
Drent, C. (2017). Dynamic dispatching and repositioning policies in service logistics networks. MSc thesis, Eindhoven University of Technology.