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An adaptive reanalysis method for genetic algorithm with application to fast truss optimization 被引量:3
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作者 Tao Xu Wenjie Zuo +2 位作者 Tianshuang Xu Guangcai Song Ruichuan Li 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2010年第2期225-234,共10页
Although the genetic algorithm (GA) for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the de... Although the genetic algorithm (GA) for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the design process, the authors present an adaptive reanalysis method for GA and its applications in the optimal design of trusses. This reanalysis technique is primarily derived from the Kirsch's combined approximations method. An iteration scheme is adopted to adaptively determine the number of basis vectors at every generation. In order to illustrate this method, three classical examples of optimal truss design are used to validate the proposed reanalysis-based design procedure. The presented numerical results demonstrate that the adaptive reanalysis technique affects very slightly the accuracy of the optimal solutions and does accelerate the design process, especially for large-scale structures. 展开更多
关键词 Truss structure adaptive reanalysis ·genetic algorithm ·Fast optimization
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