Optimization based simulation model development: Solving robustness issues

Abstract

Mathematical models are becoming popular to represent biological systems. A mathematical model can be based upon existing knowledge from scientific literature, expert opinion, and field and laboratory studies. However, there are significant issues in model development including robustness. This study therefore examines how model quality can be improved automatically using optimization approaches. Specifically, we examine how a recently developed robust model of a forest pest species, with potential application in areas such as risk prediction [3], may have its robustness further increased using optimization. Digital eco-systems provide a powerful and broader methodological foundation and support for the implementation of optimization through application of the design science method1.