IDEAS home Printed from https://ideas.repec.org/a/ids/ijmore/v22y2022i3p403-421.html
   My bibliography  Save this article

ANFIS computing and analysis of cost optimisation by upgrading service rate with N -policy, server vacation in M / M /1/∞ model

Author

Listed:
  • Anamika Jain
  • Komal Shekhawat
  • Bhoopendra Pachauri

Abstract

This study investigates an M/M/1/∞ model that emphasises the effect of various system parameters on the cost factor, with respect to upgraded service rates when the system follows N-policy and server vacation. Most often, the reason for customer dissatisfaction is the annoyingly protracted wait for the service. Therefore, given the customer's total satisfaction with the service, an upgrading in service rates is required. As a result, this study investigates the effect of different parameters on cost factors by considering the upgraded service rates, which help in better decision making. The well-known QBD process of the Markov chain is analysed using a matrix-geometric approach, and the steady-state probabilities are also observed. The system will continue in a working vacation state until the N threshold value is applied, as it follows N-policy. The adaptive neuro-fuzzy inference system (ANFIS) is utilised to approximate the nonlinear function.

Suggested Citation

  • Anamika Jain & Komal Shekhawat & Bhoopendra Pachauri, 2022. "ANFIS computing and analysis of cost optimisation by upgrading service rate with N -policy, server vacation in M / M /1/∞ model," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 22(3), pages 403-421.
  • Handle: RePEc:ids:ijmore:v:22:y:2022:i:3:p:403-421
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=124140
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijmore:v:22:y:2022:i:3:p:403-421. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=320 .

    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.