IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v237y2014i2p546-554.html
   My bibliography  Save this article

Service rate control of closed Jackson networks from game theoretic perspective

Author

Listed:
  • Xia, Li

Abstract

Game theoretic analysis of queueing systems is an important research direction of queueing theory. In this paper, we study the service rate control problem of closed Jackson networks from a game theoretic perspective. The payoff function consists of a holding cost and an operating cost. Each server optimizes its service rate control strategy to maximize its own average payoff. We formulate this problem as a non-cooperative stochastic game with multiple players. By utilizing the problem structure of closed Jackson networks, we derive a difference equation which quantifies the performance difference under any two different strategies. We prove that no matter what strategies the other servers adopt, the best response of a server is to choose its service rates on the boundary. Thus, we can limit the search of equilibrium strategy profiles from a multidimensional continuous polyhedron to the set of its vertex. We further develop an iterative algorithm to find the Nash equilibrium. Moreover, we derive the social optimum of this problem, which is compared with the equilibrium using the price of anarchy. The bounds of the price of anarchy of this problem are also obtained. Finally, simulation experiments are conducted to demonstrate the main idea of this paper.

Suggested Citation

  • Xia, Li, 2014. "Service rate control of closed Jackson networks from game theoretic perspective," European Journal of Operational Research, Elsevier, vol. 237(2), pages 546-554.
    • Handle: RePEc:eee:ejores:v:237:y:2014:i:2:p:546-554
    DOI: 10.1016/j.ejor.2014.01.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714000599
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2014.01.038?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. Baric{s} Ata & Shiri Shneorson, 2006. "Dynamic Control of an M/M/1 Service System with Adjustable Arrival and Service Rates," Management Science, INFORMS, vol. 52(11), pages 1778-1791, November.
    2. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    3. Xia, Li & Cao, Xi-Ren, 2012. "Performance optimization of queueing systems with perturbation realization," European Journal of Operational Research, Elsevier, vol. 218(2), pages 293-304.
    4. Jennifer M. George & J. Michael Harrison, 2001. "Dynamic Control of a Queue with Adjustable Service Rate," Operations Research, INFORMS, vol. 49(5), pages 720-731, October.
    5. Pengfei Guo & Refael Hassin, 2011. "Strategic Behavior and Social Optimization in Markovian Vacation Queues," Operations Research, INFORMS, vol. 59(4), pages 986-997, August.
    6. Pradeep Dubey, 1986. "Inefficiency of Nash Equilibria," Mathematics of Operations Research, INFORMS, vol. 11(1), pages 1-8, February.
    7. Laurens G. Debo & Christine Parlour & Uday Rajan, 2012. "Signaling Quality via Queues," Management Science, INFORMS, vol. 58(5), pages 876-891, May.
    8. Boudali, Olga & Economou, Antonis, 2012. "Optimal and equilibrium balking strategies in the single server Markovian queue with catastrophes," European Journal of Operational Research, Elsevier, vol. 218(3), pages 708-715.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ghosh, Souvik & Hassin, Refael, 2021. "Inefficiency in stochastic queueing systems with strategic customers," European Journal of Operational Research, Elsevier, vol. 295(1), pages 1-11.
    2. Legros, Benjamin, 2022. "The principal-agent problem for service rate event-dependency," European Journal of Operational Research, Elsevier, vol. 297(3), pages 949-963.
    3. Benjamin Legros, 2022. "The principal-agent problem for service rate event-dependency," Post-Print hal-03605421, HAL.
    4. Hoseinpour, Pooya & Jalili Marand, Ata, 2022. "Designing a service system with price- and distance-sensitive demand: A case study in mining industry," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1355-1371.

    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. Dimitrakopoulos, Y. & Burnetas, A.N., 2016. "Customer equilibrium and optimal strategies in an M/M/1 queue with dynamic service control," European Journal of Operational Research, Elsevier, vol. 252(2), pages 477-486.
    2. Wang, Jinting & Zhang, Feng, 2013. "Strategic joining in M/M/1 retrial queues," European Journal of Operational Research, Elsevier, vol. 230(1), pages 76-87.
    3. Olga Bountali & Antonis Economou, 2019. "Strategic customer behavior in a two-stage batch processing system," Queueing Systems: Theory and Applications, Springer, vol. 93(1), pages 3-29, October.
    4. Pengfei Guo & Zhe George Zhang, 2013. "Strategic Queueing Behavior and Its Impact on System Performance in Service Systems with the Congestion-Based Staffing Policy," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 118-131, September.
    5. Ziani, Sofiane & Rahmoune, Fazia & Radjef, Mohammed Said, 2015. "Customers’ strategic behavior in batch arrivals M2/M/1 queue," European Journal of Operational Research, Elsevier, vol. 247(3), pages 895-903.
    6. Bountali, Olga & Economou, Antonis, 2017. "Equilibrium joining strategies in batch service queueing systems," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1142-1151.
    7. Wang, Jinting & Zhang, Xuelu & Huang, Ping, 2017. "Strategic behavior and social optimization in a constant retrial queue with the N-policy," European Journal of Operational Research, Elsevier, vol. 256(3), pages 841-849.
    8. René Caldentey & Lawrence M. Wein, 2006. "Revenue Management of a Make-to-Stock Queue," Operations Research, INFORMS, vol. 54(5), pages 859-875, October.
    9. Pengfei Guo & Moshe Haviv & Zhenwei Luo & Yulan Wang, 2022. "Optimal queue length information disclosure when service quality is uncertain," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 1912-1927, May.
    10. Olga Boudali & Antonis Economou, 2013. "The effect of catastrophes on the strategic customer behavior in queueing systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(7), pages 571-587, October.
    11. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    12. Parlakturk, Ali & Kumar, Sunil, 2004. "Self-Interested Routing in Queueing Networks," Research Papers 1782r, Stanford University, Graduate School of Business.
    13. Odysseas Kanavetas & Barış Balcıog̃lu, 2022. "The “Sensitive” Markovian queueing system and its application for a call center problem," Annals of Operations Research, Springer, vol. 317(2), pages 651-664, October.
    14. Laurens Debo & Uday Rajan & Senthil K. Veeraraghavan, 2020. "Signaling Quality via Long Lines and Uninformative Prices," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 513-527, May.
    15. Luyi Yang & Laurens G. Debo & Varun Gupta, 2019. "Search Among Queues Under Quality Differentiation," Management Science, INFORMS, vol. 65(8), pages 3605-3623, August.
    16. Athanasia Manou & Antonis Economou & Fikri Karaesmen, 2014. "Strategic Customers in a Transportation Station: When Is It Optimal to Wait?," Operations Research, INFORMS, vol. 62(4), pages 910-925, August.
    17. Eyster, Erik & Galeotti, Andrea & Kartik, Navin & Rabin, Matthew, 2014. "Congested observational learning," Games and Economic Behavior, Elsevier, vol. 87(C), pages 519-538.
    18. Cripps, Martin W. & Thomas, Caroline D., 2019. "Strategic experimentation in queues," Theoretical Economics, Econometric Society, vol. 14(2), May.
    19. Wallace J. Hopp & Seyed M. R. Iravani & Gigi Y. Yuen, 2007. "Operations Systems with Discretionary Task Completion," Management Science, INFORMS, vol. 53(1), pages 61-77, January.
    20. Olga Bountali & Antonis Economou, 2019. "Equilibrium threshold joining strategies in partially observable batch service queueing systems," Annals of Operations Research, Springer, vol. 277(2), pages 231-253, June.

    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:ejores:v:237:y:2014:i:2:p:546-554. 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/locate/eor .

    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.