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.
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
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
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
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 8789915Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-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. E. & Hilgeman, M. J., 2019 7 p.Research output: Contribution to conference › Paper › Academic
Open Access
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, The European Conference on Machine Learning (ECML) and Principles and Practice of Knowledge Discovery in Databases (PKDD). 16 p. Arxiv 190711v1Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic
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., 1 Jun 2019, 2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019. Piscataway: Institute of Electrical and Electronics Engineers, 8 p. 8858975Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Auctions
Fuzzy Logic
Fuzzy logic
Pricing
Optimization
Machine learning based simulation optimisation for trailer management
Rijnen, D. J. F., Rhuggenaath, J., Costa, P. R. D. O. D. & Zhang, Y., 2019, (Accepted/In press) IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC). IEEE-SMCResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access
File
Light trailers
Learning systems
Feedforward neural networks
Discrete event simulation
Industry