中文摘要：

尽管为结构的优化的基因算法(GA ) 是很柔韧的，它比 optimality 标准和数学编程方法很计算地集中、因此慢。加快设计过程，在场的作者为 GA 的一个适应分析方法和它在最佳的设计的应用捆绑。这种分析技术首先从樱桃酒鈥檚 被导出联合近似方法。一个重复计划被采用适应地在每代决定基础向量的数字。以便说明这个方法，三个古典例子最佳捆绑设计被用来验证建议基于 reanalysis 的设计过程。介绍数字结果证明适应分析技术很稍微影响最佳的解决方案的精确性并且确实加速设计进程，特别为大规模结构。关键词捆绑结构 - 适应分析 - 基因算法 - 快优化工程被中国(50975121 ) 和吉林的毕业生革新资金的工程 2009-2007 的国家自然科学基金会支持大学。

英文摘要：

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.