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Research profile
Jason Rhuggenaath received his MSc. degree in Management Science and Operations Research from Erasmus University Rotterdam where he also obtained his MSc. degree in Economics and Business Economics. Currently, he pursues a Ph.D. at the School of Industrial Engineering in the Information Systems group. His research interests are data-driven optimization, sequential decision-making under uncertainty and machine learning, focusing on applications in operations management and revenue management.
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Projects
- 1 Finished
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An Automated Deep Reinforcement Learning Pipeline for Dynamic Pricing
Refaei Afshar, R., Rhuggenaath, J., Zhang, Y. & Kaymak, U., 27 Jun 2022, (E-pub ahead of print) In: IEEE Transactions on Artificial Intelligence. XX, X, 10 p.Research output: Contribution to journal › Article › Academic › peer-review
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Setting reserve prices in second-price auctions with unobserved bids
Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., 22 Mar 2022, (Accepted/In press) In: INFORMS Journal on Computing. XX, XResearch output: Contribution to journal › Article › Academic › peer-review
Open AccessFile63 Downloads (Pure) -
A Reward Shaping Approach for Reserve Price Optimization using Deep Reinforcement Learning
Refaei Afshar, R., Rhuggenaath, J., Zhang, Y. & Kaymak, U., 20 Sep 2021, 2021 International Joint Conference on Neural Networks (IJCNN). Institute of Electrical and Electronics Engineers, 8 p. 9533817Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile275 Downloads (Pure) -
Data driven design for online industrial auctions
Ye, Q. C., Rhuggenaath, J., Zhang, Y., Verwer, S. E. & Hilgeman, M. J., Jul 2021, In: Annals of Mathematics and Artificial Intelligence. 89, 7, p. 675-691 17 p.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile88 Downloads (Pure) -
Learning 2-Opt Heuristics for Routing Problems via Deep Reinforcement Learning
de O. da Costa, P. R., Rhuggenaath, J., Zhang, Y., Akcay, A. & Kaymak, U., 23 Jul 2021, In: SN Computer Science. 2, 5, 16 p., 388.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile22 Downloads (Pure)