IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v136y2021icp206-236.html
   My bibliography  Save this article

Asymptotic optimality of the generalized cμ rule under model uncertainty

Author

Listed:
  • Cohen, Asaf
  • Saha, Subhamay

Abstract

We consider a critically-loaded multiclass queueing control problem with model uncertainty. The model consists of I types of customers and a single server. At any time instant, a decision-maker (DM) allocates the server’s effort to the customers. The DM’s goal is to minimize a convex holding cost that accounts for the ambiguity with respect to the model, i.e., the arrival and service rates. For this, we consider an adversary player whose role is to choose the worst-case scenario. Specifically, we assume that the DM has a reference probability model in mind and that the cost function is formulated by the supremum over equivalent admissible probability measures to the reference measure with two components, the first is the expected holding cost, and the second one is a penalty for the adversary player for deviating from the reference model. The penalty term is formulated by a general divergence measure.

Suggested Citation

  • Cohen, Asaf & Saha, Subhamay, 2021. "Asymptotic optimality of the generalized cμ rule under model uncertainty," Stochastic Processes and their Applications, Elsevier, vol. 136(C), pages 206-236.
  • Handle: RePEc:eee:spapps:v:136:y:2021:i:c:p:206-236
    DOI: 10.1016/j.spa.2021.03.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414921000326
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spa.2021.03.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lars Peter Hansen & Thomas J Sargent, 2014. "Robust Control and Model Misspecification," World Scientific Book Chapters, in: UNCERTAINTY WITHIN ECONOMIC MODELS, chapter 6, pages 155-216, World Scientific Publishing Co. Pte. Ltd..
    2. Julio Backhoff-Veraguas & Daniel Bartl & Mathias Beiglböck & Manu Eder, 2020. "Adapted Wasserstein distances and stability in mathematical finance," Finance and Stochastics, Springer, vol. 24(3), pages 601-632, July.
    3. Rami Atar & Asaf Cohen, 2016. "A Differential Game for a Multiclass Queueing Model in the Moderate-Deviation Heavy-Traffic Regime," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1354-1380, November.
    4. Kasper Larsen & Gordan Zitkovic, 2007. "Stability of utility-maximization in incomplete markets," Papers 0706.0474, arXiv.org.
    5. Paul Glasserman & Xingbo Xu, 2014. "Robust risk measurement and model risk," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 29-58, January.
    6. Rami Atar & Subhamay Saha, 2017. "Optimality of the generalized $$\varvec{c\mu }$$ c μ rule in the moderate deviation regime," Queueing Systems: Theory and Applications, Springer, vol. 87(1), pages 113-130, October.
    7. Asaf Cohen, 2019. "Brownian Control Problems for a Multiclass M/M/1 Queueing Problem with Model Uncertainty," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 739-766, May.
    8. Pascal J. Maenhout, 2004. "Robust Portfolio Rules and Asset Pricing," The Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 951-983.
    9. Rami Atar & Haya Kaspi & Nahum Shimkin, 2014. "Fluid Limits for Many-Server Systems with Reneging Under a Priority Policy," Mathematics of Operations Research, INFORMS, vol. 39(3), pages 672-696, August.
    10. Antonis Papapantoleon & Dylan Possamai & Alexandros Saplaouras, 2018. "Stability results for martingale representations: the general case," Papers 1806.01172, arXiv.org, revised Mar 2019.
    11. Rami Atar & Anup Biswas & Haya Kaspi, 2015. "Fluid Limits of G / G /1+ G Queues Under the Nonpreemptive Earliest-Deadline-First Discipline," Mathematics of Operations Research, INFORMS, vol. 40(3), pages 683-702, March.
    12. Yuhong Xu, 2014. "Robust valuation and risk measurement under model uncertainty," Papers 1407.8024, arXiv.org.
    13. Erhan Bayraktar & Yan Dolinsky & Jia Guo, 2018. "Continuity of Utility Maximization under Weak Convergence," Papers 1811.01420, arXiv.org, revised Jun 2020.
    14. Garud N. Iyengar, 2005. "Robust Dynamic Programming," Mathematics of Operations Research, INFORMS, vol. 30(2), pages 257-280, May.
    15. Ying Chen & John J. Hasenbein, 2017. "Staffing large-scale service systems with distributional uncertainty," Queueing Systems: Theory and Applications, Springer, vol. 87(1), pages 55-79, October.
    16. Achal Bassamboo & Ramandeep S. Randhawa & Assaf Zeevi, 2010. "Capacity Sizing Under Parameter Uncertainty: Safety Staffing Principles Revisited," Management Science, INFORMS, vol. 56(10), pages 1668-1686, October.
    17. Ward Whitt, 2006. "Staffing a Call Center with Uncertain Arrival Rate and Absenteeism," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 88-102, March.
    18. Anup Biswas, 2014. "Risk-Sensitive Control for the Multiclass Many-Server Queues in the Moderate Deviation Regime," Mathematics of Operations Research, INFORMS, vol. 39(3), pages 908-929, August.
    19. Larsen, Kasper & Zitkovic, Gordan, 2007. "Stability of utility-maximization in incomplete markets," Stochastic Processes and their Applications, Elsevier, vol. 117(11), pages 1642-1662, November.
    20. Asaf Cohen, 2015. "Parameter Estimation: The Proper Way to Use Bayesian Posterior Processes with Brownian Noise," Mathematics of Operations Research, INFORMS, vol. 40(2), pages 361-389, February.
    21. Henry Lam, 2016. "Robust Sensitivity Analysis for Stochastic Systems," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1248-1275, November.
    22. Julio Backhoff-Veraguas & Daniel Bartl & Mathias Beiglbock & Manu Eder, 2019. "Adapted Wasserstein Distances and Stability in Mathematical Finance," Papers 1901.07450, arXiv.org, revised May 2020.
    23. Hernández-Hernández, Daniel & Schied, Alexander, 2007. "A control approach to robust utility maximization with logarithmic utility and time-consistent penalties," Stochastic Processes and their Applications, Elsevier, vol. 117(8), pages 980-1000, August.
    24. Aharon Ben-Tal & Dick den Hertog & Anja De Waegenaere & Bertrand Melenberg & Gijs Rennen, 2013. "Robust Solutions of Optimization Problems Affected by Uncertain Probabilities," Management Science, INFORMS, vol. 59(2), pages 341-357, April.
    25. Arnab Nilim & Laurent El Ghaoui, 2005. "Robust Control of Markov Decision Processes with Uncertain Transition Matrices," Operations Research, INFORMS, vol. 53(5), pages 780-798, October.
    26. Dylan Possamai & Guillaume Royer & Nizar Touzi, 2013. "On the Robust superhedging of measurable claims," Papers 1302.1850, arXiv.org, revised Feb 2013.
    27. Ariel Neufeld & Marcel Nutz, 2012. "Superreplication under Volatility Uncertainty for Measurable Claims," Papers 1208.6486, arXiv.org, revised Apr 2013.
    28. Yaşar Levent Koçağa & Mor Armony & Amy R. Ward, 2015. "Staffing Call Centers with Uncertain Arrival Rates and Co-sourcing," Production and Operations Management, Production and Operations Management Society, vol. 24(7), pages 1101-1117, July.
    Full references (including those not matched with items on IDEAS)

    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.
    1. Henry Lam, 2018. "Sensitivity to Serial Dependency of Input Processes: A Robust Approach," Management Science, INFORMS, vol. 64(3), pages 1311-1327, March.
    2. Jose Blanchet & Karthyek Murthy, 2019. "Quantifying Distributional Model Risk via Optimal Transport," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 565-600, May.
    3. Asaf Cohen, 2019. "Brownian Control Problems for a Multiclass M/M/1 Queueing Problem with Model Uncertainty," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 739-766, May.
    4. Soumyadip Ghosh & Henry Lam, 2019. "Robust Analysis in Stochastic Simulation: Computation and Performance Guarantees," Operations Research, INFORMS, vol. 67(1), pages 232-249, January.
    5. Henry Lam, 2016. "Robust Sensitivity Analysis for Stochastic Systems," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1248-1275, November.
    6. Aleksandrina Goeva & Henry Lam & Huajie Qian & Bo Zhang, 2019. "Optimization-Based Calibration of Simulation Input Models," Operations Research, INFORMS, vol. 67(5), pages 1362-1382, September.
    7. Zhaolin Hu & L. Jeff Hong, 2022. "Robust Simulation with Likelihood-Ratio Constrained Input Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2350-2367, July.
    8. Maximilian Blesch & Philipp Eisenhauer, 2023. "Robust Decision-Making under Risk and Ambiguity," Rationality and Competition Discussion Paper Series 463, CRC TRR 190 Rationality and Competition.
    9. Li, Jing, 2018. "Essays on model uncertainty in financial models," Other publications TiSEM 202cd910-7ef1-4db4-94ae-d, Tilburg University, School of Economics and Management.
    10. Thomas Kruse & Judith C. Schneider & Nikolaus Schweizer, 2021. "A Toolkit for Robust Risk Assessment Using F -Divergences," Management Science, INFORMS, vol. 67(10), pages 6529-6552, October.
    11. Balter, Anne G. & Pelsser, Antoon, 2020. "Pricing and hedging in incomplete markets with model uncertainty," European Journal of Operational Research, Elsevier, vol. 282(3), pages 911-925.
    12. Maximilian Blesch & Philipp Eisenhauer, 2021. "Robust decision-making under risk and ambiguity," Papers 2104.12573, arXiv.org, revised Oct 2021.
    13. Park, Kyunghyun & Wong, Hoi Ying & Yan, Tingjin, 2023. "Robust retirement and life insurance with inflation risk and model ambiguity," Insurance: Mathematics and Economics, Elsevier, vol. 110(C), pages 1-30.
    14. Roberto Baviera & Giulia Bianchi, 2019. "Model risk in mean-variance portfolio selection: an analytic solution to the worst-case approach," Papers 1902.06623, arXiv.org, revised Dec 2019.
    15. Sebastian Jaimungal & Silvana M. Pesenti & Leandro S'anchez-Betancourt, 2022. "Minimal Kullback-Leibler Divergence for Constrained L\'evy-It\^o Processes," Papers 2206.14844, arXiv.org, revised Aug 2022.
    16. Henry Lam & Clementine Mottet, 2017. "Tail Analysis Without Parametric Models: A Worst-Case Perspective," Operations Research, INFORMS, vol. 65(6), pages 1696-1711, December.
    17. Roberto Baviera & Giulia Bianchi, 2021. "Model risk in mean-variance portfolio selection: an analytic solution to the worst-case approach," Journal of Global Optimization, Springer, vol. 81(2), pages 469-491, October.
    18. Paul Glasserman & Xingbo Xu, 2013. "Robust Portfolio Control with Stochastic Factor Dynamics," Operations Research, INFORMS, vol. 61(4), pages 874-893, August.
    19. Jun-Ya Gotoh & Michael Jong Kim & Andrew E. B. Lim, 2017. "Calibration of Distributionally Robust Empirical Optimization Models," Papers 1711.06565, arXiv.org, revised May 2020.
    20. Carole Bernard & Silvana M. Pesenti & Steven Vanduffel, 2024. "Robust distortion risk measures," Mathematical Finance, Wiley Blackwell, vol. 34(3), pages 774-818, July.

    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:eee:spapps:v:136:y:2021:i:c:p:206-236. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.