EconPapers    
Economics at your fingertips  
 

Transient analysis of a Markovian N-policy queue with system disaster repair closedown setup times and control of admission

A. Azhagappan and T. Deepa

International Journal of Operational Research, 2022, vol. 44, issue 3, 279-291

Abstract: The main objective of this research work is to study the time-dependent behaviour of performance measures and probabilities for an M / M / 1 queueing model with some interesting parameters such as closedown, setup periods, disastrous breakdown of the system, repair, N-policy and different control mechanism for the arrivals when the server is under repair as well as busy. In order to reduce the cost of production and to increase the profit, the manufacturing industries follow a technique of not to start the service until the number of work pieces reaches a fixed threshold value. Shutting down the machines when no jobs are available and setting up before the commencement of service play significant contributions to reach the goals in business organisations. The probabilities of the model under consideration are derived by the method of generating function for the transient case. Some system performance measures and numerical simulations are also presented.

Keywords: N-policy queue; disaster and repair; closedown and setup times; control of admission; transient probabilities. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=124102 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:44:y:2022:i:3:p:279-291

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijores:v:44:y:2022:i:3:p:279-291