In applications within the virtual prototyping process, you cannot always reduce the complexity of the physical models and obtain numerical models which can be solved quickly. Usually, each numerical simulation takes hours or even days, and it is not possible to explore various model configurations. Due to the inherent complexity of many engineering problems, you can approximate the problem and to solve other design configurations in a smooth sub-domain by applying a surrogate model.

Starting from a reduced number of simulations, a surrogate model of the original physical problem can be used to perform various possible design configurations without computing any further analyses. These well-distributed results are used to create the metamodels. The metamodel with highest Coefficient of Prognosis (CoP) is taken to be optimal by optiSLang. The Metamodel of Optimal Prognosis (MOP) results are stored in a optiSLang monitoring database file (*.omdb) and can be used for the MOP Solver standalone tools to replace the original solver process.