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Jason Rhuggenaath, MSc

 https://orcid.org/0000-0001-5368-2947
  • 16 Citations
20172020

Research output per year

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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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Projects

Programmatic Advertising Support System (PASS)

Zhang, Y. & Rhuggenaath, J.

1/07/17 → 30/06/18

Project: Research direct

Research Output

Dynamic pricing using Thompson Sampling with fuzzy events

Rhuggenaath, J., de O. da Costa, P. R., Zhang, Y., Akcay, A. & Kaymak, U., 15 Jun 2020, Information Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Proceedings. Lesot, M-J., Vieira, S., Reformat, M. Z., Carvalho, J. P., Wilbik, A., Bouchon-Meunier, B. & Yager, R. R. (eds.). p. 653-666 14 p. (Communications in Computer and Information Science; vol. 1237 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Open Access
File
    • 15 Downloads (Pure)

    Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning

    Costa, P. R. D. O. D., Rhuggenaath, J., Zhang, Y. & Akcay, A., 3 Apr 2020.

    Research output: Working paper › Academic

    Open Access
    File
    • 75 Downloads (Pure)

    Low-regret algorithms for strategic buyers with unknown valuations in repeated posted-price auctions

    Rhuggenaath, J., de O. da Costa, P. R., Zhang, Y., Akcay, A. & Kaymak, U., 2020, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    2 Downloads (Pure)

    A heuristic policy for dynamic pricing and demand learning with limited price changes and censored demand

    Rhuggenaath, J., de Oliveira da Costa, P. R., Akcay, A., Zhang, Y. & Kaymak, U., Oct 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) . Piscataway: Institute of Electrical and Electronics Engineers, p. 3693-3698 6 p. 8914590

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    • 1 Citation (Scopus)
    26 Downloads (Pure)

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

    Rhuggenaath, J., Akcay, A., Zhang, Y. & Kaymak, U., Jun 2019, 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings. Piscataway: Institute of Electrical and Electronics Engineers, p. 2611-2619 9 p. 8789915

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

    Open Access
    File
    • 3 Citations (Scopus)
    143 Downloads (Pure)

    Courses

    Business Analytics

    1/09/15 → …

    Course

    Design of Data-Driven Business Operations

    1/09/18 → …

    Course