New estimation for the traffic intensity parameter of a single-server queueing system with finite capacity

Articles in Press

Document Type : Original Article

Author
Shahram Shahrastani Yaghoobzadeh
Department of Statistics, Payame Noor University, Tehran, Iran
10.22034/jirss.2026.2080367.1169
Abstract
In queueing theory, system is evaluated using performance merics such as the average number of of customers in the queue and system, and the average waiting time. One of the most important parameters for these metrics is the traffic intensity, which must be estimated. This paper proposes a new estimation method and compares it with existing approaches. We focus on the M/M/1/K single-server queueing model ( finite capacity) and estimate the traffic intensity using Bayesian, E-Bayesian, hierarchical Bayesian, and a new EE-Bayesian method. Beacause reducing costs and minimizing customer waiting time are central goales in queueing systems, We consider an estimator suitable if it minimizes average customer waiting time. Using Monte Carlo simulation and a real dataset, We demonstrate the superiority of the proposed method over other estimators.
Keywords
Traffic intensity parameter
E-Bayesian estimation
EE-Bayesian estimation
Average customer waiting time in the queue
M/M/1/K queueing model
Subjects
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Journal of the Iranian Statistical Society

Articles in Press, Accepted Manuscript
Available Online from 29 June 2026

  • Receive Date 09 December 2025
  • Revise Date 15 June 2026
  • Accept Date 16 June 2026