Optimizing resource allocation in m/m/1/n queues with feedback, discouraged arrivals, and reneging for enhanced service delivery

Abstract

This article presents a novel computational approach for analyzing M/M/1/N queues with feedback, discouraged arrivals, and reneging, under the first-come, first-served (FCFS) discipline. We calculate explicit transient state probabilities and represent results using symmetric tridiagonal matrix eigenvalues. Through numerical simulations, we validate our method, providing practical insights for optimizing resource allocation. Our study contributes to both theory and application, advancing queueing theory and aiding decision-makers in improving service quality and resource management.