A finite source retrial queueing inventory system with stock dependent arrival and heterogeneous servers

This article discusses a finite-source stock-dependent stochastic inventory system with multiple servers and a retrial facility. The system can store a maximum of S items, and the lifetime of each item is exponentially distributed. The primary customer arrives at the waiting hall from the finite sou...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports 2024-12, Vol.14 (1), p.30588-40, Article 30588
Main Authors: Harikrishnan, T., Jeganathan, K., Redkar, Shweta, Umamaheswari, G., Pattanaik, Balachandra, Loganathan, K.
Format: Article
Language:English
Subjects:
(s, Q) ordering policy
639/705
639/705/1041
Classical retrial policy
Customers
Humanities and Social Sciences
Impatient customers
Markov chain
Multi-server
multidisciplinary
Numerical analysis
Probability distribution
Science
Science (multidisciplinary)
Steady-state
Stochasticity
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article discusses a finite-source stock-dependent stochastic inventory system with multiple servers and a retrial facility. The system can store a maximum of S items, and the lifetime of each item is exponentially distributed. The primary customer arrives at the waiting hall from the finite source and receives service from multi-servers. The rate at which customers arrive depends on the current stock level. If the waiting hall is full during the primary customer’s arrival, he enters the finite orbit. Additionally, customers in the waiting hall may lose patience and enter the orbit. To replenish the stock, we follow the ( s ,  Q ) ordering policy. We calculate the joint probability distribution of the number of inventory items, busy servers, and number of customers in the waiting hall and orbit at a steady state. We conduct a comparative numerical analysis to determine the impact of heterogeneous and homogeneous service rates on various metrics, such as the average impatient customer rate, the fraction of successful retrials, and the average number of customers in the waiting hall and orbit.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-81593-7