• 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. 

Fingerprint Dive into the research topics where Jason Rhuggenaath is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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

  • 5 Conference contribution
  • 1 Paper

A PSO-based algorithm for reserve price optimization in online ad auctions

Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., 2019, 2019 IEEE Congress on Evolutionary Computation (CEC). Piscataway: Institute of Electrical and Electronics Engineers, p. 2611-2619 8789915

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Particle swarm optimization (PSO)
Marketing
Experiments

Data driven design for online industrial auctions

Ye, Q. C., Rhuggenaath, J., Zhang, Y., Verwer, S. & Hilgeman, M. J., 2019, (In preparation) 7 p.

Research output: Contribution to conferencePaperAcademic

File
Display devices

Data-driven policy on feasibility determination for the train shunting problem

De Oliveira Da Costa, P., Rhuggenaath, J., Zhang, Y., Akcay, A., Lee, W-J. & Kaymak, U., 2019, (Accepted/In press) The European Conference on Machine Learning (ECML) and Principles and Practice of Knowledge Discovery in Databases (PKDD). 16 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

Open Access
File
Planning
Scheduling
Parking
Learning systems
Decision making

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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
File

Courses