A generalized discrepancy and quadrature error bound
Mathematics of Computation
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Journal of Global Optimization
Optimum design of straight thin-walled box section beams for crashworthiness analysis
Finite Elements in Analysis and Design
Preform tool shape optimization and redesign based on neural network response surface methodology
Finite Elements in Analysis and Design
A residual based error estimator using radial basis functions
Finite Elements in Analysis and Design
Finite Elements in Analysis and Design
Finite Elements in Analysis and Design
Journal of Global Optimization
Metamodel-based lightweight design of B-pillar with TWB structure via support vector regression
Computers and Structures
A comparative study of metamodeling methods for multiobjective crashworthiness optimization
Computers and Structures
Moving least squares response surface approximation: Formulation and metal forming applications
Computers and Structures
Numerical analysis of the sheet metal extrusion process
Finite Elements in Analysis and Design
Optimal crashworthiness design of a spot-welded thin-walled hat section
Finite Elements in Analysis and Design
Optimal design of aeroengine turbine disc based on kriging surrogate models
Computers and Structures
Artificial Bee Colony algorithm for optimization of truss structures
Applied Soft Computing
A multi-surrogate approximation method for metamodeling
Engineering with Computers
Multi-fidelity optimization for sheet metal forming process
Structural and Multidisciplinary Optimization
Crashworthiness design of vehicle by using multiobjective robust optimization
Structural and Multidisciplinary Optimization
A hybrid OC-GA approach for fast and global truss optimization with frequency constraints
Applied Soft Computing
Expert Systems with Applications: An International Journal
Structural and Multidisciplinary Optimization
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Optimization integrated with either one step solver (low fidelity model) or incremental nonlinear finite element solver (high fidelity model) has respectively gained increasing popularity in the design of sheet metal forming process to improve product quality and shorten lead time. However, the one step solver directly incorporated with optimization may result in inadequate design precision, while the incremental method often leads to a prohibitively low computing efficiency. In order to take the full advantages of both the one step solver and incremental solver, we present a variable fidelity algorithm which integrates the one step solver with incremental solver for optimizing sheet metal forming process in this study. In the variable fidelity method established, we need to determine the difference between the two solvers at some predefined experimental points firstly, and then constructing a corrected function using surrogate models for compensating the responses of the one step solver at other points. Different surrogate models, such as response surface methodology (RSM), Kriging (KRG), radial basis function (RBF) and support vector regression (SVR), are considered and compared for best modeling accuracy in this paper. The compensated low fidelity model can be used as a high fidelity model in the optimization process. In this study, we adopt the artificial bee colony (ABC) algorithm to obtain the global optimum. To demonstrate the capability of the variable fidelity method combined with the ABC algorithm, the optimal design of draw-bead restraining forces for an automobile inner panel is exemplified herein. The results show that the optimization with variable fidelity method presented significantly improves the computational efficiency and formability of the workpiece.