Abstract:
Queuing is the inevitable aspect of our day-to-day life, occurring whenever the
demand for relevant service exceeds the capacity or the speed of available servers.
The Queuing theory provides a systematic framework to analyse such situations,
enabling the design of efficient and effective service systems that minimise the
waiting times while optimising the resource utilisation. This study applies the queuing
theory to investigate the waiting line dynamics at a university cafeteria in Colombo,
Sri Lanka, during peak hours on Sundays. Data was collected through a direct
observation approach over two separate Sundays, focusing on the breakfast rush
(10:00–10:30) and the lunch peak (12:15–12:45), both operating with the same
number of cashiers and servers. Using the Microsoft Excel-based M/M/1 simulation
model for preliminary statistical analysis and the Any Logic simulation software for
dynamic modelling, we examined the arrival rates, service times, and system
performance under varying demand conditions. The results indeed revealed notable
differences in arrival patterns and the average queue lengths between breakfast and
the lunch sessions, with the lunch showing higher arrival intensity and longer wait
times. On Day 01, the average waiting time was 63.05 seconds in the morning and
79.81 seconds at lunch, while on Day 02 it increased to 102.31 seconds in the morning
and 162.42 seconds at lunch. The simulation experiments further explored the
potential improvements, including adjusted staffing levels, effective serving
strategies, and the optimised service time distribution. By combining real-world data
with the simulation-based modelling, this research not only highlights the
applicability of queuing theory to the real-world service environments but also indeed
provides practical recommendations to enhance efficiency in the cafeteria operations.
This research finding shows simulating cafeteria data using Any logic can be used to
improve service quality.
