Structural design employing a sequential approximation optimization approach

•An improved SAO is proposed to solve structural design problems.•An adaptive sampling strategy is developed as one of the improvements to SAO.•An enhanced RBF is proposed as the other improvement to SAO.•The enhanced SAO shows good performance for structural design problems.

This paper presents an improved sequential approximation optimization (SAO) algorithm that is suitable for structural design optimization tasks. First, an adaptive sampling strategy is proposed to balance between the competence to locate the global optimum and the computation efficiency in the optimization process. Furthermore, an original estimation of the width of the basis function is proposed based on the local density of sampling points, which enhances the RBF for the SAO. The efficacy of the enhanced SAO algorithm is validated using several benchmark structural design cases and the computing costs are substantially reduced in comparison to other optimization algorithms.