An Approach Towards Predicting the Computational Runtime Reduction from Discrete-Event Simulation Model Simplification Operations

Model simplification is the process of developing a simplified version of an existing discrete-event simulation (DES) to study the performance of specific system subcomponents relevant to the analysis. The simplified model is referred to as a ‘metasimulation’. A widely used model simplification operation is abstraction, which involves replacing the subcomponents, not core to the analysis, from the parent DES model with random variables representing the lengths of stay in said subcomponents. However, the one-time computational cost of developing metasimulations via abstraction can itself be considerable, as the approach necessitates executing the parent model for generating the necessary data for developing the metasimulation. Thus, this study proposes a queuing-theoretic approach for estimating the computational runtime reduction (CRR) achieved through abstraction, wherein the prediction of CRR precedes the development of the metasimulation. Towards this, we present preliminary results from applying this approach for simplification of DES models made up of M/M/n workstations.