ABSTRACT
This chapter models a barber shop as a queueing system using a continuous time Markov chain. The goal is to identify which particular reconfiguration of the barber shop would be most beneficial to customers.
A theoretic overview of concepts related to stationary distributions of continuous Markov chains is given before solutions approaches are given in both R and Python. This is done using Numpy in Python and expm in R for all the underlying linear algebra.
