The Optimization of Curve Based on Genetic Algorithm and Energy Method

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Abstract:

An optimization method based on genetic algorithm and energy method is presented to construct a fairing curve network from unconnected sectional curves. The curve’s quality is evaluated by its energy. The parameters of the intersecting points on existing curves are adopted as variable and genetic algorithm is used to optimize the energy of curve based on multi-parent crossover operator. The examples show that the interpolated surface of optimized curve network has good quality than other methods, which proves our method actually improves curve networks’ quality.

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227-230

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September 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Kuragano J, Suzuki H and Takarada: Journal of the Japan Society of Precision Engineering Vol. 69 (2003), p.1264

Google Scholar

[2] Moreton H, S C, Quin. In: Proceedings of the first ACM symposium on Solid modeling foundations and CAD/CAM applications, Austin, Texas, United States ACM, (1991).

DOI: 10.1145/112515.112553

Google Scholar

[3] Wallner J, Pottmann H and Hofer M. In: ACM SIGGRAPH 2005 Sketches, Los Angeles, California: ACM Press(2005), p.32.

DOI: 10.1145/1187112.1187149

Google Scholar

[4] Wesche G and Seidel H P. In: Proceedings of the ACM symposium on Virtual reality software and technology, New York, NY, USA: ACM Press, (2001), p.167.

Google Scholar

[5] Schaefer S, Warren J and Zorin D. In: Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing, Nice, France: ACM Press, (2004), p.103.

DOI: 10.1145/1057432.1057447

Google Scholar

[6] Levin A. In: Proceedings of the ACM SIGGRAPH Conference on Computer Graphics, Los Angeles, CA, USA: ACM, (1999), p.57.

Google Scholar

[7] Welch W and Witkin A: Computer Graphics Vol. 26 (1992), p.157.

Google Scholar

[8] Shigeyoshi Tsutsui, Masayuki Yamamura and Takahide Higuchi. In: Proceedings of the Genetic and Evolutionary Computation Conference Orlando, Florida, USA, (1999), p.657.

Google Scholar