基于离散变量的大跨越输电塔架构不同优化方法研究

INVESTIGATION ON STRUCTURAL OPTIMIZATION OF LONG-SPAN TRANSMISSION TOWER BASED ON DISCRETE VARIABLES

为了解决大跨越输电塔结构的优化问题,提出了基于离散变量的拓扑组合优化方案和复杂构型组合优化方案,并采用自适应遗传算法进行结构的优化分析。首先采用罚函数形式确定遗传算法的适应度函数,然后确定遗传编码的转换方案以及自适应交叉和变异算子,在此基础上研究了四种优化方案,即截面尺寸优化方案、形状组合优化方案、拓扑组合优化方案、复杂构型组合优化方案。并对于拓扑组合优化提出了拓扑优化准则,对于复杂构型组合优化提出了层次化优化方法。优化结果表明:拓扑组合优化方案与复杂构型组合优化方案的优化效果明显好于截面尺寸优化方案和形状组合优化方案,由于复杂构型组合优化方案本身包含有拓扑的改变,其对原始构造改变较大,故优化结果最好。

In order to solve the structural optimization problem of long-span transmission tower, topology combination optimization （TCO） method and configuration combination optimization （CCO） method based on discrete variables are presented respectively. The adaptive genetic algorithm （AGA） is used to search optimization solution. Firstly the fitness function of AGA is obtained by using the penalty function. Then the change schemes of genetic coding are proposed and the adaptive crossover and mutation operators are acquired. Finally, four optimization methods are discussed using the AGA, including rod cross-section optimization （RCSO） method, shape combination optimization （SCO） method, TCO method and CCO method. The topology optimization rules are presented for the TCO method, and the layering optimization rules are presented for the CCO method. The simulation results demonstrate that the optimization results of the proposed TCO method and CCO method are obviously better than those of the RCSO method and SCO method. Complex change in the configuration of tower is permitted by The CCO method, thus the optimization result is the best in these methods.