Learning and data-driven optimization in queues with strategic customers
Author
Abstract
Suggested Citation
DOI: 10.1007/s11134-022-09816-0
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Aurélien Garivier & Pierre Ménard & Gilles Stoltz, 2019. "Explore First, Exploit Next: The True Shape of Regret in Bandit Problems," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 377-399, May.
- Apostolos N. Burnetas & Michael N. Katehakis, 1997. "Optimal Adaptive Policies for Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 222-255, February.
- Ying Chen & John J. Hasenbein, 2020. "Knowledge, congestion, and economics: Parameter uncertainty in Naor’s model," Queueing Systems: Theory and Applications, Springer, vol. 96(1), pages 83-99, October.
- Nahum Shimkin & Adam Shwartz, 1996. "Asymptotically Efficient Adaptive Strategies in Repeated Games Part II. Asymptotic Optimality," Mathematics of Operations Research, INFORMS, vol. 21(2), pages 487-512, May.
- Dimitris Bertsimas & Nathan Kallus, 2020. "From Predictive to Prescriptive Analytics," Management Science, INFORMS, vol. 66(3), pages 1025-1044, March.
- Eyal Even-Dar & Sham. M. Kakade & Yishay Mansour, 2009. "Online Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 34(3), pages 726-736, August.
- Apostolos Burnetas & Antonis Economou & George Vasiliadis, 2017. "Strategic customer behavior in a queueing system with delayed observations," Queueing Systems: Theory and Applications, Springer, vol. 86(3), pages 389-418, August.
- Panayotis Mertikopoulos & William H. Sandholm, 2016. "Learning in Games via Reinforcement and Regularization," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1297-1324, November.
- Moshe Haviv & Ramandeep S. Randhawa, 2014. "Pricing in Queues Without Demand Information," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 401-411, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- van Eekelen, Wouter, 2023. "Distributionally robust views on queues and related stochastic models," Other publications TiSEM 9b99fc05-9d68-48eb-ae8c-9, Tilburg University, School of Economics and Management.
- Hassin, Refael & Haviv, Moshe & Oz, Binyamin, 2023. "Strategic behavior in queues with arrival rate uncertainty," European Journal of Operational Research, Elsevier, vol. 309(1), pages 217-224.
- Inchi Hu & Chi-Wen Jevons Lee, 2003. "Bayesian Adaptive Stochastic Process Termination," Mathematics of Operations Research, INFORMS, vol. 28(2), pages 361-381, May.
- Serrano, Breno & Minner, Stefan & Schiffer, Maximilian & Vidal, Thibaut, 2024. "Bilevel optimization for feature selection in the data-driven newsvendor problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 703-714.
- Keliang Wang & Leonardo Lozano & Carlos Cardonha & David Bergman, 2023. "Optimizing over an Ensemble of Trained Neural Networks," INFORMS Journal on Computing, INFORMS, vol. 35(3), pages 652-674, May.
- Meng Qi & Ying Cao & Zuo-Jun (Max) Shen, 2022. "Distributionally Robust Conditional Quantile Prediction with Fixed Design," Management Science, INFORMS, vol. 68(3), pages 1639-1658, March.
- Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.
- Athanassios N. Avramidis & Arnoud V. Boer, 2021. "Dynamic pricing with finite price sets: a non-parametric approach," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(1), pages 1-34, August.
- Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
- Xinchang Wang & Sigrún Andradóttir & Hayriye Ayhan, 2019. "Optimal pricing for tandem queues with finite buffers," Queueing Systems: Theory and Applications, Springer, vol. 92(3), pages 323-396, August.
- Andrew Butler & Roy Kwon, 2021. "Efficient differentiable quadratic programming layers: an ADMM approach," Papers 2112.07464, arXiv.org.
- Liu, Congzheng & Letchford, Adam N. & Svetunkov, Ivan, 2022. "Newsvendor problems: An integrated method for estimation and optimisation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 590-601.
- Corredera, Alberto & Ruiz, Carlos, 2023. "Prescriptive selection of machine learning hyperparameters with applications in power markets: Retailer’s optimal trading," European Journal of Operational Research, Elsevier, vol. 306(1), pages 370-388.
- Shuaian Wang & Xuecheng Tian, 2023. "A Deficiency of the Predict-Then-Optimize Framework: Decreased Decision Quality with Increased Data Size," Mathematics, MDPI, vol. 11(15), pages 1-9, July.
- Toon Vanderschueren & Robert Boute & Tim Verdonck & Bart Baesens & Wouter Verbeke, 2022. "Prescriptive maintenance with causal machine learning," Papers 2206.01562, arXiv.org.
- Andrew Butler & Roy H. Kwon, 2021. "Data-driven integration of norm-penalized mean-variance portfolios," Papers 2112.07016, arXiv.org, revised Nov 2022.
- Sel, Burakhan & Minner, Stefan, 2022. "A hedging policy for seaborne forward freight markets based on probabilistic forecasts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
- Mertikopoulos, Panayotis & Sandholm, William H., 2018. "Riemannian game dynamics," Journal of Economic Theory, Elsevier, vol. 177(C), pages 315-364.
- Dmitry B. Rokhlin, 2020. "Relative utility bounds for empirically optimal portfolios," Papers 2006.05204, arXiv.org.
- Robert Engel & Pablo Fernandez & Antonio Ruiz-Cortes & Aly Megahed & Juan Ojeda-Perez, 2022. "SLA-aware operational efficiency in AI-enabled service chains: challenges ahead," Information Systems and e-Business Management, Springer, vol. 20(1), pages 199-221, March.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:queues:v:100:y:2022:i:3:d:10.1007_s11134-022-09816-0. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.