We consider M/M/c/K (K ≥ c ≥ 1) retrial queues with two types of nonpersistent customers, which are motivated from modelling of service systems such as call centers. Arriving customers that see the system fully occupied either join the orbit or abandon receiving service forever. After an exponentially distributed time in the orbit, each customer either abandons the system forever or retries to ...

The aim of this paper is to investigate a multiserver retrial queueing system with a finite number of heterogeneous sources of calls. The novelty of the investigation is the heterogeneity of the sources, that is every source is characterized by different arrival, retrial and service rates. All random variables involved in the model construction are assumed to be exponentially distributed and in...

In this paper a single server retrial queue with a finite number of heterogeneous sources of calls is investigated. It is assumed when a given source is idle it will generate a primary call after an exponentially distributed time. If the server is free at the time of the request’s arrival then the call starts to be served. The service time is also exponentially distributed. During the service t...

In call centers, call blending consists in the mixing of incoming and outgoing call activity. Artalejo and Phung-Duc recently provided an apt model for such a setting, with a two way communication retrial queue. However, by assuming a classical (proportional) retrial rate for the incoming calls, the outgoing call activity is largely blocked when many incoming calls are in orbit, which may be un...

The present investigation deals with the performance prediction of finite Markovian retrial queues with unreliable server. The arrivals of the customers follow geometric distribution while the service pattern follows exponential distribution. The customers are served in two stages i.e. first essential service (FES) which is compulsory for all the arriving customers and second optional service (...

Retrial queueing systems are characterized by the requirement that customers finding the service area busy must join the retrial group and reapply for service at random intervals. This paper deals with the M/G/1 retrial queue subjected to breakdowns. We use its stochastic decomposition property to approximate the model performance in the case of general retrial times.