Performance Analysis of a Queuing Dynamics Model in a Supermarket to Optimize the Efficiency: Case of Monte Carlo Simulation

Queuing theory is a mathematical approach used to analyze waiting lines or queues and to optimize their performances. It has numerous applications in different fields, such as telecommunications, transportation, healthcare, and retail sectors. In this paper, we analyze the data of a supermarket. This research paper focuses on employing Monte Carlo Simulation to evaluate the queuing dynamics and determine the optimal number of servers required to achieve maximum efficiency within the surveyed supermarket. The results serve as a valuable resource for supermarket operators to make data-driven decisions to minimize customer waiting times, optimize staff utilization and improve overall service efficiency. The proposed queuing model and analytical framework can be extended and applied to other retail environments, thus contributing to the advancement of retail queuing theory.