Application of multiserver queueing to call centres

Majakwara, Jacob (2009) Application of multiserver queueing to call centres. Masters thesis, Rhodes University.




The simplest and most widely used queueing model in call centres is the MMk system, sometimes referred to as Erlang-C. For many applications the model is an over-simplification. Erlang-C model ignores among other things busy signals, customer impatience and services that span multiple visits. Although the Erlang-C formula is easily implemented, it is not easy to obtain insight from its answers (for example, to find an approximate answer to questions such as “how many additional agents do I need if the arrival rate doubles?”). An approximation of the Erlang-C formula that gives structural insight into this type of question would be of use to better understand economies of scale in call centre operations. Erlang-C based predictions can also turn out highly inaccurate because of violations of underlying assumptions and these violations are not straightforward to model. For example, non-exponential service times lead one to the MGk queue which, in stark contrast to the MMk system, is difficult to analyse. This thesis deals mainly with the general MGIk model with abandonment. The arrival process conforms to a Poisson process, service durations are independent and identically distributed with a general distribution, there are k servers, and independent and identically distributed customer abandoning times with a general distribution. This thesis will endeavour to analyse call centres using MGIk model with abandonment and the data to be used will be simulated using EZSIM-software. The paper by Brown et al [3] entitled “Statistical Analysis of a Telephone Call Centre: A Queueing-Science Perspective,” will be the basis upon which this thesis is built.

Item Type:Thesis (Masters)
Uncontrolled Keywords:Call centers, ERLANG (Computer program language), Queuing theory
Subjects:Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions:Faculty > Faculty of Commerce > Statistics
Faculty > Faculty of Science > Statistics
Supervisors:Szyszkowski, I
ID Code:1889
Deposited By: Mrs Carol Perold
Deposited On:09 Feb 2011 09:08
Last Modified:06 Jan 2012 16:21
231 full-text download(s) since 09 Feb 2011 09:08
183 full-text download(s) in the past 12 months
More statistics...

Repository Staff Only: item control page