Enhancing discrete event modelling by interfacing expert systems and simulation models.

This thesis investigates the representation of operational decision makers within simulation modelling. Artificial Intelligence concepts, such as expert systems focus on the problem of representing, in high-level code, complex real-world decision making problems. The author therefore proposes that the use of expert system technology may provide an improved means of representing operational decision tasks and that as a consequence, apriori possibilities may exist in the context of model experimentation based on alternative operational policies. The thesis further investigates the nature of operational decision making and the potential need to represent within a model, inter-dependencies between decision makers. A prototype system called ESSIM is developed which comprises of two interlinked components, a discrete event simulation module and expert system module. The benefits of the proposed approach are then assessed by comparing the functionally of ESSIM with conventional modelling techniques. The comparison is carried out by developing three alternative models of an automated container port, one of these using ESSIM. Experiments were then devised and executed which seek to draw conclusions on the thesis proposal