Publication

Abstract : This paper presents an analysis of a study that uses queueing theory to investigate the rate at which customers arrive and receive service in a supermarket over the course of one week during predetermined time intervals. The data collected over a one-week period includes the number of customers arriving at specific intervals, along with their corresponding service and arrival rates. To examine several performance variables and determine how frequently consumers waited in queue, the M/M/1 model is utilised and cost analyses are conducted to determine the waiting cost, the utilisation factor, and other relevant metrics. The study focused on peak days that were observed in the one-week data, such as Monday, Wednesday, Friday, and Saturday. The M/M/2 model is used as an assumptions model to determine which model was more suitable for the supermarket during the peak days. The result of this paper will provide insights into the effectiveness of the M/M/1 and M/M/2 models for predicting customer waiting times and resource utilisation at the supermarket. Based on the findings of this study, the supermarket will be able to make informed decisions about staffing and resource allocation during peak hours. This study provides insights for supermarket managers on how to optimise their queueing systems to improve t he customer experience and increase revenue.