Destructive identification approaches are no longer in favor since the advent of nondestructive evaluation approaches, as they are accurate, rapid, and cheap. Researchers are devoted to improving the accuracy, rate of convergence, and cost of such approaches, which depend greatly on the types of vibrational experiments conducted and the types of forward and inverse methods used in numerical section. Therefore, this article presents a review on the development of nondestructive vibrational evaluation approaches in identifying the elastic constants of composite plates, in experimental and numerical manners in order to enlighten researchers with the current trends of nondestructive vibrational approaches

The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. Besides, distinctive crossover and mutation operators are introduced, in which, two types of mutation operators, namely, standard mutation and refined mutation are suggested. In early iterations, standard mutation is utilized collaboratively with the concept of unrepeated tours of ACO to evade local entrapment, while refined mutation is used in later iterations to supplement the exploitative search, which is mainly controlled by particle swarm optimization. The proposed method has been validated in solving test functions and well-known engineering design problems. It exhibits a great global search capability even in the presence of non-linearity, multimodality and constraints, involving a large number of dimensions as well as large search areas.