Introduction
This chapter is concerned with the review of relevant
literature aimed at proper understanding of the problem under investigation.
The chapter consist of empirical review, theoretical framework and conceptual
framework.
Matthias (2011) conducted a study on restaurant queuing
model. The aim of the study was to show that queuing theory satisfies the model
when tested with a real-life scenario. In line with the objectives of this he
obtained the data from a restaurant in Jakarta. He then derived the arrival
rate, service rate, utilization rate, waiting time in the queue and the
probability of potential customers to balk based on the data using Little’s
theorem and M/M/1 queuing model. He discovered that this theory is applicable
for the restaurant. He then concluded that the average arrival rate will be
lesser than and the service rate will be greater if it is on weekdays since the
average numbers of customers is less compared to those of weekend.
Using queuing theory to analyze the government 4-h completion time
target in accident and emergency
departments by L. Mayhew. D. Smith
Smith (2007) conducted a study using queuing theory to
analyze the governments 4-b completion time target in Accident and Emergency (A
& E) departments in the light of government target of completing and discharging
98% patient inside 4-h. It illustrated how output can be used to visualize and
interprete the 4 –h government target in a simple way and how the model can be
used to assess the practical achievability of A&E targets in the futures. In line with our objectives was able to
determine, the average time required to complete the treatment of patient, the
percentage of patient treated and medical assessment of the unit (that is the
utilization rate. The paper found that A&E targets have resulted in
significant improvements in completion times and thus deal with a major source
of complaint by users of the National Health service in the UK. It suggested
that whilst some of this improvement is attributable to better management, some
are also due to the way some patients in A&E are designated and therefore
counted through the system.