Structural Optimization Through GeneticAdaptation And Regeneration
Structural Optimization Through GeneticAdaptation And Regeneration
复制标题
通过遗传适应和再生进行结构优化
DOI：
10.2495/op950111
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发表时间：
1970
期刊：
影响因子：
--
通讯作者：
J. Kintzel
中科院分区：
文献类型：
--
作者：
J. Bolander;Y. Kobashi;J. Kintzel
将遗传算法应用于以高度不确定桁架网络为代表的结构构件的刚度最大化问题。桁架单元的截面面积是需要优化的设计变量。与使用一组静态解参数的传统算法不同，在进化过程中减少了设计变量的数量。收缩设计变量空间的决定是基于对设计总体的调查，其中考虑了每个遗传成分的功能。在减少变量数量后，用随机值初始化新的总体，并继续优化。这种再生过程极大地提高了性能，既加快了收敛速度，又达到了更优化的结果。总体方法的有效性在很大程度上取决于对再生过程的谨慎使用。
Genetic algorithms are applied to maximizing the stiffness of structural members represented by highly indeterminate truss networks. Truss element cross-sectional areas are the design variables to be optimized. Unlike conventional algorithms which use a static set of solution parameters, the number of design variables is reduced during the evolutionary process. Decisions to contract the design variable space are based on surveys of the design population, where the functionality of each genetic component is taken into consideration. Upon reducing the number of variables, a new population is initialized with random values and the optimization continues. This regeneration process dramatically improves performance, both in speeding convergence and in reaching more optimal results. The effectiveness of the overall approach depends largely on careful use of the regeneration process.