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Statistical Analysis Of The Queuing System In A Bus Terminal
[A CASE STUDY OF NEKEDE BUS TERMINAL]
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Queuing theory is generally considered a branch of
operations research because the results are often used when making
business decisions about the resources needed to provide service. It is
applicable in a wide variety of situations that they may be encountered
in business, commerce, industry, public service and engineering.
Applications are frequently port and telecommunication. Queuing theory
is directly applicable to intelligent transportation systems, call
centers, and traffic flow.
ELEMENTS OF A QUEUING MODEL
The
principal actors in a queuing situation are the customer and the server.
Customers are generated from a source. On arrival at a service
facility, they can start service immediately or wait in a queue if the
facility is busy. When a facility completes a service, it automatically
“pulls†a waiting customer, if any, from the queue. If the queue is
empty, the facility becomes idle until a new customer arrives.
customers, and the service is described by the service time per
customer.
1.1 STATEMENT OF PROBLEM
Waiting for service is part
of our daily life. We wait to eat in restaurants, we “queue up†at the
check-out counters in grocery stores, and we “line up†for service in
post offices. And the waiting phenomenon is not an experience limited
to human beings only: Jobs wait to be processed on a machine, planes
circle in a stack before given permission to land at an airport, and
cars can stop at traffic lights. Waiting can not be eliminated
completely without incurring inordinate expenses and the goal is reduce
its adverse impact to “tolerable†levels. Basic single server model
assumes customers are arriving at Poisson arrival rate with exponential
service times.
It therefore becomes an interest for the
researcher to find out what can be done to reduce the queue and to
identify the distribution which the arrival and service time follows
using Nekede bus terminal as a case study.
1.2 AIMS AND OBJECTIVES OF THE STUDY
The major aims and objective of this study are as follows:
1. To find out if the arrival of buses in a terminal follow Poisson distribution
2. To find out if the service times are exponential.
3. To find out if increasing the number of servers (terminals) would reduce the queue/waiting time
4. To identify if the queue operates in a steady state condition.
5.
To identify, show, then suggest through empirically backed decision how
the management of Nekede bus terminal go about the reduction of waiting
time of vehicles in the terminal.
RESEARCH QUESTIONS
1. What are the causes of queuing in the terminal?
2. Does the arrival of buses in the terminal follow Poisson distribution?
3. Do their service times follow exponential?
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ABSRACT - [ Total Page(s): 1 ]The need to reduce the length of queue (waiting time) forms the basis of this research. This project work centers on the queuing system witnessed at the Nekede bus terminal; and a single serve queuing system was adopted in the analysis. The basic aim and objectives of this research is to identify the distribution of the arrival and service and finding out if increasing the number services (terminal) would tend to reduce the waiting time in the system. Different probability distribution where use ... Continue reading---
