Curve and surface fitting with splines
Curve and surface fitting with splines
The approximation power of moving least-squares
Mathematics of Computation
Bias-specified robust design optimizaion and its analytical solutions
Computers and Industrial Engineering - Special issue: Selected papers from the 31st international conference on computers & industrial engineering
A review of optimization techniques in metal cutting processes
Computers and Industrial Engineering
Bias-specified robust design optimization: A generalized mean squared error approach
Computers and Industrial Engineering
Moving least squares response surface approximation: Formulation and metal forming applications
Computers and Structures
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In general, optimization techniques involve numerous repeated objective function evaluations. As a consequence, optimization times can become very large depending on the complexity of the model to be optimized. This manuscript describes the development of an adaptive response surface method for optimization of computation-intensive models, capable of reducing optimization times. The response model to be optimized is not built from a pre-defined number of design experiments but is adapted and refined during the optimization routine. Different approximation models are applicable in combination with the developed optimization technique. The proposed optimization technique is evaluated on a standard test problem as well as a finite element model design optimization with multiple parameters.