Design of Composite Structure Optimization Model Based on Particle Swarm Optimization

A new nested-niche technique for optimization design of composite laminated structure

“…The evolutionary algorithms were widely used in the optimization of composite laminated structure because of their advantages of simple theory and strong adaptability. Özkan et al [2] performed a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) to solve the structural optimization problem of a composite Phase II wind turbine blade; In the research of Dong et al [3], the particle swarm optimization algorithm was used to optimize the structural of ship composite materials; In reference [4], Particle swarm optimization algorithm (PSO), genetic algorithm (GA), and hunger games search optimization algorithm(HGS) were used to determine the best stacking angle value on the disc plate; Tran et al [5] presented a new approach as an integration of deep neural networks (DNN) into differential evolution (DE) for frequency optimization of laminated functionally graded carbon nanotube (FG-CNT)-reinforced composite quadrilateral plates. But the evolutionary algorithms have the problem of converging to an undesired local solution (premature convergence) when the objective function is multimodal, this restricts the application of these algorithms.…”