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.
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© 1996 Springer-Verlag Berlin Heidelberg
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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
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DOI: https://doi.org/10.1007/BFb0032772
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