The Society For Modeling and Simulation International (SCS)
Abstract
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
