A survey of curve and surface methods in CAGD
Computer Aided Geometric Design
Curves and surfaces for computer aided geometric design (3rd ed.): a practical guide
Curves and surfaces for computer aided geometric design (3rd ed.): a practical guide
Automatic reconstruction of B-spline surfaces of arbitrary topological type
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
An Introduction to 3D Computer Vision Techniques and Algorithms
An Introduction to 3D Computer Vision Techniques and Algorithms
GRID technology for structural analysis
Advances in Engineering Software
Essential windows communication foundation: for .net framework 3.5
Essential windows communication foundation: for .net framework 3.5
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
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Shape optimization is numerically very intensive due to multidisciplinary objectives and constraints, many shape variables, non linear models, geometric infeasibility of candidate designs, etc. It involves participation of numerical optimizers, computer- aided geometric modelers and subject-related simulators as well as their coupling at the process- and data levels. This paper develops a simple experimental workflow which employs existing commercial software for computer-aided design, finite element analysis and evolutionary optimization modules. It sets up parallel execution of multiple simulators to reduce the execution time, which is implemented inexpensively by means of a self-made .net- based cluster. Shape optimization is introduced in the generic context of 'enhanced' reverse engineering with optimization whereby the initial solution can be obtained by 3D optical scanning and parameterization of an existing solution.