Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Taxonomy of Global Optimization Methods Based on Response Surfaces
Journal of Global Optimization
Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models
Journal of Global Optimization
An effective co-evolutionary particle swarm optimization for constrained engineering design problems
Engineering Applications of Artificial Intelligence
Particle swarm approach for structural design optimization
Computers and Structures
Journal of Global Optimization
Size optimization of space trusses using Big Bang-Big Crunch algorithm
Computers and Structures
Genetic algorithms and finite element coupling for mechanical optimization
Advances in Engineering Software
Structural optimization based on CAD-CAE integration and metamodeling techniques
Computer-Aided Design
Optimization of forging processes using Finite Element simulations
Structural and Multidisciplinary Optimization
Comparison of evolutionary-based optimization algorithms for structural design optimization
Engineering Applications of Artificial Intelligence
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
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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.