A trapezoidal approach to cost optimization in M/M/1 queueing systems

The study addresses the problem of cost optimization in an M/M/1 queueing system by incorporating fuzzy logic to manage uncertainties in system parameters. By modeling imprecise inputs such as arrival rate, service rate and cost factors as fuzzy numbers, the research aims to develop a more realistic and flexible approach to minimizing the total operating cost of the system. In order to deliver more realistic findings for the model under discussion than crisp results, we want to create the total cost function and further compute the total optimal cost of the system in a fuzzy environment. Lastly, the model's numerical and graphical analysis has been done for trapezoidal numbers.