Retrial bulk queue with state dependent arrival and negative customers

Abstract

In this investigation, the single server retrial queue is studied under the assumption that the arrival of the positive customers occur in bulk with state dependent rates. The server may breakdown during the essential and optional services due to arrival of negative customers. The combined supplementary variable and generating function approach is used to analyze the mathematical model and to find the queueing characteristics. The cost function has been constructed to determine the optimal number of parameters involved for providing the desired efficiency to the system. The numerical results for various performance indices are presented to examine the system behavior. The Adaptive Neuro Fuzzy Inference System (ANFIS) technique which is the combination of neural network and fuzzy logic has been used to design a fuzzy inference model for the retrial queueing system. The neuro fuzzy based numerical results are generated for the mean queue length.