System dynamics simulation and optimization with fuzzy logic

This paper presents a novel and practical approach for integrating simulation and optimization of system dynamics (SD) models using Matlab and Simulink. The Matlab platform allows much freedom in customizing and implementing global search techniques such as genetic algorithms (GA) and artificial intelligence constructs like fuzzy logic. The Simulink platform allows complex nonlinear dynamic models to be specified rapidly. In this work we demonstrate how to combine the GA parameter search, fuzzy logic expert input and SD modeling to arrive at better strategies for decision making. This approach to optimization is illustrated using the classical market growth-model and produces very competitive good results.