  This paper reports on continuing research into the modelling of an order
picking process within a Crossdocking distribution centre using Simulation
Optimisation. The aim of this project is to optimise a discrete event
simulation model and to understand factors that affect finding its optimal
performance. Our initial investigation revealed that the precision of the
selected simulation output performance measure and the number of replications
required for the evaluation of the optimisation objective function through
simulation influences the ability of the optimisation technique. We
experimented with Common Random Numbers, in order to improve the precision of
our simulation output performance measure, and intended to use the number of
replications utilised for this purpose as the initial number of replications
for the optimisation of our Crossdocking distribution centre simulation model.
Our results demonstrate that we can improve the precision of our selected
simulation output performance measure value using Common Random Numbers at
various levels of replications. Furthermore, after optimising our Crossdocking
distribution centre simulation model, we are able to achieve optimal
performance using fewer simulations runs for the simulation model which uses
Common Random Numbers as compared to the simulation model which does not use
Common Random Numbers.
