Laminate stacking sequence optimization with strength constraints using two-level approximations and adaptive genetic algorithm

A stacking sequence optimization method, which is conducted on the basis of a ground laminate and utilizes a two-level approximation as well as a genetic algorithm (GA), was developed before by the authors. Compared with general GAs, this method shows lower computational costs while reaching a high level of practical feasibility. However, the published work did not involve problems constrained with a strength requirement, which is essential for laminate structures subject to multiple loading conditions. Thus, in the present study, this approach is extended to implement strength constraints for laminate stacking sequence optimizations. First, to avoid the selection of some control parameters in the GA as well as to improve its performance, the standard genetic algorithm is modified with adaptive schemes in the fitness function and GA operators. Furthermore, by adopting the first-ply failure criterion and considering the stresses/strains for each layer in the ground laminate, the concept of temporal deletion techniques is proposed to extend this approach for handling optimization problems with strength constraints. Moreover, by combining the optimizer with the general finite element software MSC. Patran/Nastran, an optimization framework is established to conduct the optimization easily. Numerical examples are performed in repeated runs to illustrate the performance of the modified approaches in the GA as well as the feasibility and efficiency of this optimization system.