Composite structures optimization using hybrid genetic algorithm for space applications

Abstract

The aim of this study is to develop a hybrid genetic algorithm (H-GA) that combines a genetic algorithm (GA) and a descent local search technique to pursue the optimization of a sandwich composite inter-stage skirt located in the upper bound of the launcher. Total number of plies forming the sandwich composite skin and fiber orientations (predefined ply angles) are considered as design variables. The H-GA is chosen as an optimization tool thanks to its ability to deal with discrete optimization problems, of which the design of composites stacking is an example. First, the proposed approach is presented and explained. Then, its performances are compared and discussed against those offered by the classical GA.The aim of this study is to develop a hybrid genetic algorithm (H-GA) that combines a genetic algorithm (GA) and a descent local search technique to pursue the optimization of a sandwich composite inter-stage skirt located in the upper bound of the launcher. Total number of plies forming the sandwich composite skin and fiber orientations (predefined ply angles) are considered as design variables. The H-GA is chosen as an optimization tool thanks to its ability to deal with discrete optimization problems, of which the design of composites stacking is an example. First, the proposed approach is presented and explained. Then, its performances are compared and discussed against those offered by the classical GA.