A new nondeterministic method for optimal selection of master degrees of freedom for dynamic condensation based on evolutionary optimization

The following paper presents a new method for choosing a set of master degrees of freedom for the process of dynamic condensation in order to reduce a finite element model. The general rule is that the more degrees of freedom are eliminated, the more accurate the reduced model is. However, eliminating different subsets (of equal sizes) of degrees of freedom may influence the accuracy differently. Therefore, choosing an optimal subset is crucial. The presented method is based on multicriterial evolutionary optimization which makes it the first nondeterministic approach based on computational optimization technique for this application.