改进遗传算法在桁架拓扑优化中的应用

Application of improved genetic algorithm in truss topology optimization

基于桁架拓扑优化,对遗传算法提出了一些改进措施,形成了一种高效综合的遗传算法。在桁架的截面尺寸和拓扑结构混合设计中,对尺寸变量和拓扑变量分别进行二进制编码、交叉和变异,得到桁架拓扑结构和杆件截面尺寸的初解,适当降低尺寸变量编码精度,以加快算法的收敛速度。然后对截面尺寸重新编码,以较高的尺寸精度进行搜索,为了防止陷入局部最优解,取部分初解加入新的父代。算例表明,该算法对离散变量的桁架拓扑优化是快速有效的。

Based on the topology optimization of truss, the genetic algorithm （GA） was improved more efficient. In the design of size and topological structure of the truss, binary encoding, crossover and mutation for size and topology variables were adopted separately and the initial solution was gained, with the accuracy of the size variable coding properly reduced to speed up the convergence of the GA. In order to prevent trapping in local optimal solution, a portion of initial solution was added to the new parents, and then the size of section was recoded and the final solution was searched in a better precision. Examples show that the method is effective to the topology optimization design of truss structures with discrete variables.