Surrogate based optimization of functionally graded plates using radial basis functions

•A surrogate model based on radial basis functions (RBF) is presented to speed up the optimization of functionally graded (FG) plates.•The material gradation is defined using B-Spline to enhance design flexibility.•A novel constraint is proposed to ensure a smooth variation of material gradation through the plate thickness.•Different methods to evaluate the width of basis functions are compared.•Two infill criteria based on the expected improvement approach are used to update the surrogate model.•Excellent results were obtained in maximization of the buckling load and the fundamental frequency of FG plates. This work presents an efficient methodology for optimum design of functionally graded plates. Isogeometric analysis is used to evaluate the structural responses and the material gradation is described using B-Splines to enhance design flexibility. A constraint is included in the optimization model to ensure a smooth material gradation. In order to improve the computational efficiency of the optimization process, a surrogate model based on Radial Basis Functions is used to accurately approximate the structural responses. Different methods to define the width of basis functions based on analytical and cross-validation techniques are adopted and compared. Two infill criteria based on the expected improvement technique are used to continuously improve the surrogate model accuracy by balancing both the local and global searches. The accuracy and efficiency of the proposed approaches are assessed through a set of problems involving the maximization of the buckling load and the fundamental frequency of functionally graded plates, showing excellent results.