A Technique for Constrained Optimization of Cross-ply Laminates using a New Variant of Genetic Algorithm - Zhang, Huiyao; Yokoyama, Atsushi (International journal of advanced computer science & applications, 2021)
The main challenge presented by the design of laminated composite material is the laminate layup, involving a set of fiber orientations, composite material systems, and stacking sequences. In nature, it is a combinatorial optimization problem with constraints that can be solved by the genetic algorithm. The traditional approach to solve a constrained problem is reformulating the objective function. In the present study, a new variant of the genetic algorithm is proposed for the design of composite material by using a mix of selection strategies, instead of modifying the objective function. To check the feasibility of a laminate subject to in-plane loading, the effect of the fiber orientation angles and material components on the first ply failure is studied. The algorithm has been validated by successfully optimizing the design of cross-ply laminate under different in-plane loading cases. The results obtained by this algorithm are better than works in related literature.