Implementation of Queuing Theory in Counters Serving the Public Service Sector

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Published: Mar 1, 2024
DOI: https://doi.org/10.29070/fmh2h439
Keywords:
Queuing Theory, Public Service Sector, Service Counters, Waiting Time, Queue Length, M/M/1 Model, M/M/c Model, Service Efficiency, Resource Optimization, Operational Management

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Authors

Mohit Kumar

Research Scholar, Department of Mathematics, Baba Mastnath University, Haryana

Dr. Naveen Kumar

Professor, Department of Mathematics, Baba Mastnath University, Haryana

Abstract

The effectiveness of counters in the public service sector is of critical importance in ensuring that people get services in a timely manner and to their satisfaction. Waiting line theory, which is a mathematical study of waiting lines, provides useful tools for analyzing, designing, and optimizing service systems in situations where the arrival of customers and the procedures involved in providing service are intrinsically unpredictable. The purpose of this research is to investigate the use of queuing theory models, such as M/M/1, M/M/c, and limited capacity systems, in a variety of public service contexts. These settings include government offices, banks, hospitals, and transportation hubs. The use of these models allows the study to identify important performance indicators such as the average waiting time, the length of the line, and the usage of the system. Additionally, the research provides solutions to reduce delays and improve the efficiency of service. The research reveals, via the use of simulation and real-time case studies, how queue management strategies, when based on queuing theory, have the potential to greatly enhance service quality, minimize operational bottlenecks, and contribute to improved resource allocation. Not only do the results shed light on the practical consequences of mathematical modeling in public administration, but they also provide advice to policymakers and managers on how to integrate data-driven decision-making in service delivery.

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Issue

Vol. 21 No. 1 (2024): Journal of Advances in Science and Technology (JAST)

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