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| Truss topology optimization by using multi-point approximation and GA |
| Revised:January 14, 2003 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20046134 |
| KeyWord:topology optimization,multi|point approximation,genetic algorithm |
| Dong Yongfang Huang Hai~* |
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| Abstract: |
| A new method for truss topology optimization based on the multi|point approximate function and the genetic algorithm (GA) is proposed. In the work, an optimization model including continuously cross|sectional size variables and discrete topology variables is created, and then a series of first level approximate problems of the created structural optimization problem are constructed using the multi|point approximate function. To solve the first|level approximate problems with mixed|variables, a layered optimization strategy is introduced. The topology variables of the trusses are optimized through GA in the external layer, and the cross|sectional areas of bars are optimized in the internal layer through a series of second level approximate problems that can be solved by the dual method. The required structural analyses for truss topology optimization can be dramatically decreased as GA is only used to solve the approximate problems in the external layer where no structural analysis is needed. On the other hand, a relatively small number of species is taken in GA as the design variables of cross|sectional areas are determined in internal layer. The results of the classical examples of truss topology optimization show that the proposed method can reach the optimum solutions after an extremely few structural analyses. |
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