Page 105 - DCAP601_SIMULATION_AND_MODELING

Unit 7: Simulation of Queuing System (I)

Using the data collected as the input to the discrete-event simulation program, we set up two Notes
simulators for predicting the behaviour of a single-channel queue and a multiple-channels
queue respectively.
The purpose of using simulation technique to analyze the collected data is to avoid costly design
errors, and to analyze the behaviours of the existing systems. More importantly, simulation can
be used to predict the performance of the existing system when the input parameters such as the
arrival rate and service rate are changed.
Simulation technique can also be applied to analyze the behaviours of system which has not
even been created yet.

Materials Used

The first phase of this project is data collection. We used stopwatches to time the inter-arrival
time and service time, and calculate the average timings as shown in Tables 7.1 and 7.2.
Table 7.1: Data Collected at Choa Chu Kang and Clementi
MacDonalds from 15:30 to 16:30 and 10:30 to 11:30

Inter-Arrival Time (sec) Service Time (sec)
Average 48 70

Table 7.2: Data Collected at Taman Warna and Clementi POSB
from 15:30 to 16:30 and 15:10 to 16:10 respectively

Inter-Arrival Time/s Service Time/s
Average 30 130

Methods

Discrete-event Approach

Discrete event is a technique used to model the real-world scenarios. In the queuing model two
types of events are used, namely arrival and departure. The arrival corresponds to the real-
world event when a customer reaches a service station, and the departure corresponds to the
event when the customer leaves. Due to the causality constraints, the arrival event for a customer
must be executed before its departure event.
Each event has a timestamp corresponding to the wall-clock time when it occurs. Discrete-event
technique has been widely used in the simulation of communication and transportation systems,
such as telephone networks, seaport and airport operations, etc.
What if POSB changes its queue to multiple-channels and McDonalds changes its queue to
single-channel?
We first validate the data collected and compare the deviation of the observed and predicated
queue length, waiting time and wait probability. As the simulation results follow closely the
observed values, we brought up the question of whether McDonalds and POSB will benefit if
they switched their queuing systems. The simulator was used to find out the answers.

The changes to the input data are as follows: To convert from a single-channel queue to a
multiple-channels queue for n servers we will have to divide the arrival rate by n because the

LOVELY PROFESSIONAL UNIVERSITY 99