Texture optimization of rolled aluminum alloy sheets using a genetic algorithm

In this paper, a genetic algorithm is adopted to solve texture optimization problems for aluminum alloy sheets. Five typical texture components in aluminum alloy sheets, i.e. Cu, Brass, S, Cube and Goss, are considered. In general, the most appropriate volume fractions of these texture components for a user-defined particular requirement, e.g. the smallest possible in-plane anisotropy, or the largest possible formability, are unknown a priori. First, we describe a genetic algorithm with real-valued genes, which is called the real-coded GA, to solve texture optimization problems. Then, this algorithm is used to search for optimum textures that satisfy the requirements of smallest possible in-plane anisotropy and largest possible formability in biaxial stretch, as examples, to verify the efficiency of the method.