Analysis Of Fuzzy Queueing Models To Optimize The Average System Size In Packet-Switching Network

Abstract

Single server batch arrival retry queue with varying modes of breakdowns and two stages of restoration is considered under a fuzzy situation. Assuming the arrival, working, retry, breakdown, and repair rates are fuzzy; a mathematical programming method is proposed to construct the membership function for the average system size of the prescribed model. To convert a fuzzy repairable retrial queue into a family of crisp queues, the alpha-cut technique and Zadeh's extension concept are utilised. Trapezoidal fuzzy numbers are used to illustrate the strength of the proposed approach. Ranking fuzzy numbers play a huge role in decision-making under fuzzy conditions. This ranking method is the most reliable, simple to apply, and used to find the defuzzification of the syatem measures. A particular application in packet-switching network is given for a better understanding of the model.