Finding the Important Factors in Large Discrete-Event Simulation : Sequential Bifurcation and its Applications

This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors. The experiments are guided by sequential bifurcation. This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated through a first-order polynomial possibly augmented with two-factor interactions. The method is explained and illustrated through three related discrete-event simulation models. These models represent three supply chain configurations, studied for an Ericsson factory in Sweden. After simulating 21 scenarios (factor combinations) each replicated five times to account for noise, a shortlist with the 11 most important factors is identified for the biggest of the three simulation models