Recital facts of M X / G /1 queues with setup time, phases of service, and vacation
S. Maragathasundari and
K. Karthikeyan
International Journal of Mathematics in Operational Research, 2025, vol. 31, issue 2, 241-262
Abstract:
Researching group queueing systems that combine setup time and vacation work stages into a single server service is the aim of this MX/G/1 queueing study. In this queueing system, arrival time follows the Poisson distribution and service time follows a general distribution. The model is well equipped with setup time phases to do both a key maintenance task during the break and the necessary server pre-processing job. Additionally, the system is unavailable during the disruption because service disruptions are inevitable. The aforementioned mathematical queueing problem is solved using the supplemental variable technique, and the system's performance metrics are obtained. From the calculated probability generation function of queue size at a random time for the different system states, we extract performance measures such as the server's probability of idle time, the utilisation factor, the average queue length, and the average wait time. It is backed by methods for numerical portrayal, graphic representation, and real-world applications. This paradigm is entirely legal due to its practical use and algebraic demarcation mechanism. The graph provides precise readings of the implemented limitations.
Keywords: non-Markovian queueing problem; batch arrival; supplementary variable technique; setup time stages; vacation; service interruption. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=147022 (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:ijmore:v:31:y:2025:i:2:p:241-262
Access Statistics for this article
More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().