Design structures subjected to uncertainty using wide bezier curve

Genetic algorithms (GA) do have some advantages over gradient-based methods for solving topology design optimization problems. However, their success depends largely on the geometric representation used. In this work, an morphological representation of geometry using wide Bezier curve is applied and evaluated to be efficient and effective in producing good results via a structure design problem subjected to uncertainty. A wide Bezier curve is a Bezier curve with width or cross section. Based on the morphology of living creatures, a geometric representation scheme has been developed that works by specifying a skeleton which defines the underlying topology/connectivity of a structural continuum together with segments of material surrounding the skeleton. This scheme facilitates the transmission of topological and shape characteristics across generations in the evolutionary process and amplify the representation variability. The proposed scheme coupled with a GA is presented to perform topology optimization.