Abstract
This paper describes work on two different aspects of the application of genetic algorithms to component design. Namely structural design optimisation and the evolution of free-form 3D shapes. On the first aspect, a thorough comparison of ten different search techniques applied to a wing-box design optimisation problem is described. The techniques used vary from deterministic gradient descent to stochastic Simulated Annealing (SA) and Genetic Algorithms (GAs). The stochastic techniques produced as good solutions as the best found by the deterministic techniques. However, only the stochastic techniques consistently produced very good solutions every run. Significantly, only a distributed genetic algorithm (DGA) and hybrid methods (SA with gradient descent, DGA with gradient descent) had a reliable fast decent to good regions of solution space. On the free-form 3D shape aspect, an interactive systems for exploring the evolution of 3D shapes is described. An important element of the systems is its use of a shape description language based on superquadric primitives and global deformations of these primitives.
Preview
Unable to display preview. Download preview PDF.
References
A. Barr. Superquadrics and angle preserving transformations. IEEE Computer Graphics and Applications, 1(1):11–23, 1981.
A. Barr. Global and local deformations of solid primitives. Computer Graphics, 18(3):21–30, 1984.
R. Collins and D. Jefferson. Selection in massively parallel genetic algorithms. In R. K. Belew and L. B. Booker, editors, Proceedings of the Fourth Intl. Conf. on Genetic Algorithms, ICGA-91, pages 249–256. Morgan Kaufmann, 1991.
L. Davis. The Handbook of Genetic Algorithms. Van Nostrand Reinhold, 1990.
R. Dawkins. The Blind Watchmaker. Harlow Logman, 1986.
M. Gardiner. The superellipse: a curve that lies between the ellipse and the rectangle. Scientific American, 213:222–234, 1965.
David E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, Massachusetts, USA, 1989.
G. Jermy. Evolutionary design of three dimensional objects. Master's thesis, School of Cognitive and Computing Sciences, University of Sussex, 1995.
A. J. Keane. Structural design for enhanced noise performance using genetic algorithms and other optimisation techniques. In R. Albrecht, C. Reeves, and N. Steele, editors, Proceedings of ANNGA93, the Intl. Conf. on Neural Networks and Genetic Algorithms, pages 536–543. Springer-Verlag, 1993.
S. Kirkpatrich, C. Gelatt, and M. Vecchi. Optimisation by simulated annealing. Science, 220:671–680, 1983.
M. McIlhagga, P. Husbands, and R. Ives. A comparison of search techniques on a wing-box optimisation problem. In Proceedings of PPSN IV. Springer Verlag, 1996.
D. Powell and M. Skolnick. Using genetic algorithms in engineering design optimization with non-linear constraints. In S. Forrest, editor, Proc. 5th Int. Conf. on GAs, pages 424–431. Morgan Kaufmann, 1993.
W. Press, W. Vetterling, S. Teukolsky, and B. Flannery. Numerical recipes in C (2/e). CUP, 1992.
J. Snyder. Generative Modelling for Computer Graphics and CAD. Academic Press, 1992.
K. Unnikrishnan and K. Venugopal. Learning in connectionist networks using the alopex algorithm. In Proceedings IJCNN 1992, pages I-926–I-931. IEEE Press, 1992.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Husbands, P., Jermy, G., McIlhagga, M., Ives, R. (1996). Two applications of genetic algorithms to component design. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1996. Lecture Notes in Computer Science, vol 1143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032772
Download citation
DOI: https://doi.org/10.1007/BFb0032772
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61749-5
Online ISBN: 978-3-540-70671-7
eBook Packages: Springer Book Archive