• 0 Citations
20172019
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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

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Projects 2017 2018

Programmatic Advertising Support System (PASS)

Jansen, R., Jansen, R., Zhang, Y., Gerrits, E. & Rhuggenaath, J.

1/07/1730/06/18

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 proceedingConference contributionAcademicpeer-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 proceedingConference contributionAcademicpeer-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 proceedingConference contributionAcademicpeer-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 proceedingConference contributionAcademicpeer-review

Open Access
File
Integer programming
Decision trees
Mathematical programming
Fuzzy inference
Linear programming