Analysis of Different Simulation Techniques for Solving Queueing Theory Problems

Abstract

This study deals with applying and analysing various simulation techniques in solving a problem from queueing theory (mass service system). The motivation for this study is to understand how different characteristics are obtained when using different probability distributions to generate input data. The starting point for this study is unpaired data on the number of units entering the system per unit time and the service time of requests. We modelled the changing intensity of input requirements using step change in intensity and polynomial regression. The service time was modelled by empirical, triangular, and gamma distribution. Combining these approaches, we created six models of a mass service system and identified their characteristics. The characteristics obtained by each model varied very little within statistical variation.