Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Pattern Search Methods for Linearly Constrained Minimization
SIAM Journal on Optimization
Preform tool shape optimization and redesign based on neural network response surface methodology
Finite Elements in Analysis and Design
Development of an adaptive response surface method for optimization of computation-intensive models
Computers and Industrial Engineering
Sensitive couture for interactive garment modeling and editing
ACM SIGGRAPH 2011 papers
Calcolo: a quarterly on numerical analysis and theory of computation
Multi-fidelity optimization for sheet metal forming process
Structural and Multidisciplinary Optimization
Structural and Multidisciplinary Optimization
Advances in Engineering Software
Structural and Multidisciplinary Optimization
Finite element modelling and optimisation of net-shape metal forming processes with uncertainties
Computers and Structures
The numerical solution of the non-linear integro-differential equations based on the meshless method
Journal of Computational and Applied Mathematics
The optimal design of sheet metal forming processes: application to the clinching of thin sheets
International Journal of Computer Applications in Technology
Finite Elements in Analysis and Design
Importance measure analysis with epistemic uncertainty and its moving least squares solution
Computers & Mathematics with Applications
Towards a space reduction approach for efficient structural shape optimization
Structural and Multidisciplinary Optimization
A Framework for Moving Least Squares Method with Total Variation Minimizing Regularization
Journal of Mathematical Imaging and Vision
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We focus on a successive response surface method for the optimization problems. The response surfaces are built using Moving Least Squares approximations constructed within a moving region of interest. Our first approach is an extension of pattern search algorithms with a fixed pattern panned and zoomed in a continuous manner across the design space. In the second one, the region of interest moves across a predefined discrete grid of authorized experimental designs. Two examples of the sheet metal forming process are used to demonstrate the robustness of the method. We use the one-step Inverse Approach as a surrogate model during the optimization. The final designs is validated with Stampack commercial code based on Explicit Dynamics Approach.