In discussing self-organizing neural networks, to some extent a large-scale network is assumed in order to achieve generality and adaptability. This paper discusses an optimal structurization method for a nonlinear network, based on a self-organizing algorithm with a two-layer structure. The basic s
A regional genetic algorithm for the discrete optimal design of truss structures
✍ Scribed by A. A. Groenwold; N. Stander; J. A. Snyman
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 144 KB
- Volume
- 44
- Category
- Article
- ISSN
- 0029-5981
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✦ Synopsis
A regional genetic algorithm (R-GA) is used for the discrete optimal design of truss structures. The chromosomes are selected from a sub-region centred on the continuous optimum. This approach replaces genetic rebirth as previously proposed by other authors, thereby signiÿcantly reducing computational costs. As a pure discrete method, the R-GA method does not require heuristic arguments or approximations. This makes the algorithm highly e ective when buckling and slenderness constraints with scatter in the data are introduced. A large set of numerical test examples is used to illustrate the capabilities of the method. The algorithm is shown to be e ective and robust, making it suitable for the optimal design of very large truss structures.
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