Projects per year
Personal profile
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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Economics
Business & Economics
Operations research
Business & Economics
Operations management
Business & Economics
Decision making under uncertainty
Business & Economics
Sequential decision making
Business & Economics
Information systems
Business & Economics
Industrial engineering
Business & Economics
Revenue management
Business & Economics
Network
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Projects 2017 2018
- 1 Finished
Programmatic Advertising Support System (PASS)
Jansen, R., Jansen, R., Zhang, Y., Gerrits, E. & Rhuggenaath, J.
1/07/17 → 30/06/18
Project: Research direct
Research Output 2018 2019
- 4 Conference contribution
A PSO-based algorithm for reserve price optimization in online ad auctions
Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., 2019, (Accepted/In press) 2019 IEEE Congress on Evolutionary Computation. Institute of Electrical and Electronics Engineers (IEEE)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Fuzzy logic based pricing combined with adaptive search for reserve price optimization in online ad auctions
Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., 2019, (Accepted/In press) 2019 IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers (IEEE)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Optimizing reserve prices for publishers in online ad auctions
Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., 11 Apr 2019, (Accepted/In press) 2019 IEEE Conference on Computational Intelligence for Financial Engineering and Economics. Institute of Electrical and Electronics Engineers (IEEE)Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Learning fuzzy decision trees using integer programming
Rhuggenaath, J. S., Zhang, Y., Akcay, A., Kaymak, U. & Verwer, S. E., 2018, 2018 IEEE International Conference on Fuzzy Systems. Piscataway: Institute of Electrical and Electronics Engineers (IEEE), p. 312-319 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Integer programming
Decision trees
Mathematical programming
Fuzzy inference
Linear programming