Sensitivity analysis and optimization of system dynamics models: Regression analysis and statistical design of experiments

Abstract This paper discusses what‐if analysis and optimization of system dynamics models. These problems are solved, using the statistical techniques of regression analysis and Design of Experiments (DOE). These issues are illustrated by applying the statistical techniques to a system dynamics model for coal transportation, taken from Wolstenholme's book System Enquiry: a System Dynamics Approach (1990). The regression analysis uses the least‐squares algorithm. DOE uses classic designs, namely, factorials and central composite designs. Compared with intuitive approaches, DOE is more efficient: DOE gives more accurate estimators of input effects. Moreover DOE is more effective: interactions among inputs are estimable too. The system dynamics model is also optimized, using a heuristic that is inspired by Response Surface Methodology (RSM) but that also accounts for constraints. Conclusions are presented for the case study, and general principles are derived. References are given for further study.