Analysis of Markov Multiserver Retrial Queues with Negative Arrivals
Queueing Systems: Theory and Applications
A Multi-Server Retrial Queue with BMAP Arrivals and Group Services
Queueing Systems: Theory and Applications
M/M/1 Queueing systems with inventory
Queueing Systems: Theory and Applications
A perishable inventory system with service facilities and retrial customers
Computers and Industrial Engineering
A perishable inventory system with retrial demands and a finite population
Journal of Computational and Applied Mathematics
A multi-server perishable inventory system with negative customer
Computers and Industrial Engineering
Homogeneous finite-source retrial queues with server subject to breakdowns and repairs
Mathematical and Computer Modelling: An International Journal
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In this article, we study a continuous review retrial inventory system with a finite source of customers and identical multiple servers in parallel. The customers arrive according a quasi-random process. The customers demand unit item and the demanded items are delivered after performing some service the duration of which is distributed as exponential. The ordering policy is according to (s, S) policy. The lead times for the orders are assumed to have independent and identical exponential distributions. The arriving customer who finds all servers are busy or all items are in service, joins an orbit. These orbiting customer competes for service by sending out signals at random times until she finds a free server and at least one item is not in the service. The inter-retrial times are exponentially distributed with parameter depending on the number of customers in the orbit. The joint probability distribution of the number of customer in the orbit, the number of busy servers and the inventory level is obtained in the steady state case. The Laplace-Stieltjes transform of the waiting time distribution and the moments of the waiting time distribution are calculated. Various measures of stationary system performance are computed and the total expected cost per unit time is calculated. The results are illustrated numerically.