IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i20p4265-d1258668.html
   My bibliography  Save this article

Numerical Computation of Distributions in Finite-State Inhomogeneous Continuous Time Markov Chains, Based on Ergodicity Bounds and Piecewise Constant Approximation

Author

Listed:
  • Yacov Satin

    (Department of Applied Mathematics, Vologda State University, 160000 Vologda, Russia)

  • Rostislav Razumchik

    (Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 119133 Moscow, Russia)

  • Ilya Usov

    (Department of Applied Mathematics, Vologda State University, 160000 Vologda, Russia)

  • Alexander Zeifman

    (Department of Applied Mathematics, Vologda State University, 160000 Vologda, Russia
    Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 119133 Moscow, Russia
    Vologda Research Center, Russian Academy of Sciences, 160014 Vologda, Russia
    Moscow Center for Fundamental and Applied Mathematics, Moscow State University, 119991 Moscow, Russia)

Abstract

In this paper it is shown, that if a possibly inhomogeneous Markov chain with continuous time and finite state space is weakly ergodic and all the entries of its intensity matrix are locally integrable, then, using available results from the perturbation theory, its time-dependent probability characteristics can be approximately obtained from another Markov chain, having piecewise constant intensities and the same state space. The approximation error (the taxicab distance between the state probability distributions) is provided. It is shown how the Cauchy operator and the state probability distribution for an arbitrary initial condition can be calculated. The findings are illustrated with the numerical examples.

Suggested Citation

  • Yacov Satin & Rostislav Razumchik & Ilya Usov & Alexander Zeifman, 2023. "Numerical Computation of Distributions in Finite-State Inhomogeneous Continuous Time Markov Chains, Based on Ergodicity Bounds and Piecewise Constant Approximation," Mathematics, MDPI, vol. 11(20), pages 1-12, October.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:20:p:4265-:d:1258668
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/20/4265/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/20/4265/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Linda Green & Peter Kolesar, 1991. "The Pointwise Stationary Approximation for Queues with Nonstationary Arrivals," Management Science, INFORMS, vol. 37(1), pages 84-97, January.
    2. Alexander Zeifman & Victor Korolev & Yacov Satin, 2020. "Two Approaches to the Construction of Perturbation Bounds for Continuous-Time Markov Chains," Mathematics, MDPI, vol. 8(2), pages 1-25, February.
    3. Ward Whitt & Wei You, 2019. "Time-Varying Robust Queueing," Operations Research, INFORMS, vol. 67(6), pages 1766-1782, November.
    4. M. Arns & P. Buchholz & A. Panchenko, 2010. "On the Numerical Analysis of Inhomogeneous Continuous-Time Markov Chains," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 416-432, August.
    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. Alexander Zeifman & Yacov Satin & Ivan Kovalev & Rostislav Razumchik & Victor Korolev, 2020. "Facilitating Numerical Solutions of Inhomogeneous Continuous Time Markov Chains Using Ergodicity Bounds Obtained with Logarithmic Norm Method," Mathematics, MDPI, vol. 9(1), pages 1-20, December.
    2. Yacov Satin & Rostislav Razumchik & Ivan Kovalev & Alexander Zeifman, 2023. "Ergodicity and Related Bounds for One Particular Class of Markovian Time—Varying Queues with Heterogeneous Servers and Customer’s Impatience," Mathematics, MDPI, vol. 11(9), pages 1-15, April.
    3. Schwarz, Justus Arne & Selinka, Gregor & Stolletz, Raik, 2016. "Performance analysis of time-dependent queueing systems: Survey and classification," Omega, Elsevier, vol. 63(C), pages 170-189.
    4. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2006. "Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method," Operations Research, INFORMS, vol. 54(3), pages 419-435, June.
    5. Ward Whitt, 2007. "What you should know about queueing models to set staffing requirements in service systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(5), pages 476-484, August.
    6. Niyirora, Jerome & Zhuang, Jun, 2017. "Fluid approximations and control of queues in emergency departments," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1110-1124.
    7. Ilya Usov & Yacov Satin & Alexander Zeifman & Victor Korolev, 2022. "Ergodicity Bounds and Limiting Characteristics for a Modified Prendiville Model," Mathematics, MDPI, vol. 10(23), pages 1-14, November.
    8. Xi Chen & Dave Worthington, 2017. "Staffing of time-varying queues using a geometric discrete time modelling approach," Annals of Operations Research, Springer, vol. 252(1), pages 63-84, May.
    9. Ward Whitt & Wei You, 2022. "New decomposition approximations for queueing networks," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 365-367, April.
    10. Yifan Liu & Lawrence M. Wein, 2008. "A Queueing Analysis to Determine How Many Additional Beds Are Needed for the Detention and Removal of Illegal Aliens," Management Science, INFORMS, vol. 54(1), pages 1-15, January.
    11. Legros, Benjamin & Fransoo, Jan C., 2023. "Admission and pricing optimization of on-street parking with delivery bays," Other publications TiSEM 6d41ee5c-27dc-4d34-aff1-4, Tilburg University, School of Economics and Management.
    12. Abhishek, & Legros, Benjamin & Fransoo, Jan C., 2021. "Performance evaluation of stochastic systems with dedicated delivery bays and general on-street parking," Other publications TiSEM 09ed9572-d59c-4f28-a9c4-b, Tilburg University, School of Economics and Management.
    13. Neil Keon & G. “Anand” Anandalingam, 2005. "A New Pricing Model for Competitive Telecommunications Services Using Congestion Discounts," INFORMS Journal on Computing, INFORMS, vol. 17(2), pages 248-262, May.
    14. Andriy Shapoval & Eva K. Lee, 2022. "Managing Guest Flow in Georgia Aquarium After the Dolphin Tales Show Opening," SN Operations Research Forum, Springer, vol. 3(3), pages 1-21, September.
    15. Achal Bassamboo & J. Michael Harrison & Assaf Zeevi, 2009. "Pointwise Stationary Fluid Models for Stochastic Processing Networks," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 70-89, August.
    16. Mor Armony & Constantinos Maglaras, 2004. "On Customer Contact Centers with a Call-Back Option: Customer Decisions, Routing Rules, and System Design," Operations Research, INFORMS, vol. 52(2), pages 271-292, April.
    17. Legros, Benjamin & Fransoo, Jan & Jouini, Oualid, 2024. "How to optimize container withholding decisions for reuse in the hinterland?," Other publications TiSEM 8c64b894-e9ee-415a-b396-1, Tilburg University, School of Economics and Management.
    18. Omar Besbes & Costis Maglaras, 2009. "Revenue Optimization for a Make-to-Order Queue in an Uncertain Market Environment," Operations Research, INFORMS, vol. 57(6), pages 1438-1450, December.
    19. Abhishek Abhishek & Benjamin Legros & Jan Fransoo, 2021. "Performance Evaluation of Stochastic Systems with Dedicated Delivery Bays and General On-Street Parking," Post-Print hal-03605434, HAL.
    20. J. Michael Harrison & Assaf Zeevi, 2005. "A Method for Staffing Large Call Centers Based on Stochastic Fluid Models," Manufacturing & Service Operations Management, INFORMS, vol. 7(1), pages 20-36, September.

    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:gam:jmathe:v:11:y:2023:i:20:p:4265-:d:1258668. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.