Bayesian, E-Bayesian and hierarchical Bayesian estimations for optimization of traffic intensity in the M/M/m/K queue based on fuzzy index
نویسندگان
1 Department of Statistics, Payame Noor University, Tehran, Iran
2 Department of Statistics, Payame Noor University, Tehran, Iran
3 Department of Statistics, Payame Noor University, Tehran, Iran
doi
10.22034/jsmta.2025.22918.1175چکیده
This paper focuses on the M/M/m/K queuing model, where inter-arrival and service times follow exponential distributions. We discuss the fuzzy average degree of customer satisfaction and evaluate traffic intensity based on a fuzzy index, using Bayesian, E-Bayesian, and hierarchical Bayesian methods, applying the general entropy loss function. Additionally, the maximum likelihood estimation method is utilized for estimation. To compare the performances of the proposed estimation methods, a Monte Carlo simulation is conducted. Evaluation criteria, such as the cost function and the average customer satisfaction index, are used to select the most appropriate estimation method for the present paper. Finally, a numerical example is provided to determine the most suitable estimator.
