改进的FOA算法在通用桥式起重机轻量化设计中的应用

The Improved FOA Algorithm Applied in the Shaft Bracket Structure Optimization Design Optimization Design

针对传统FOA算法全局收敛能力差、易陷入局部极值的缺陷,提出了具有混沌映射及协同进化功能的改进果蝇算法。首先利用Logistic混沌映射功能在整个收敛域范围内搜索并初始化果蝇种群,保证算法的全局计算能力,然后根据当前果蝇个体的位置赋予搜索的方向与距离,以期全面提高算法的计算速度。采用两个优化函数测试改进后算法优化的特性,优化计算的结果显示了该算法具有良好的全局优化能力,在通用桥式起重机金属结构轻量化设计中的成功应用,体现了该算法在结构设计轻量化方面的优越性。

In view of the poor global convergence ability of traditional Fruit Fly Optimization Algorithm （FOA algorithm）, and it is easily trapped in local minima, an improved FOA algorithm is proposed which has the function of chaotic mapping and cooperative co-evolution. Firstly, using the function of Logistic chaotic mapping for searching and initialize the drosophila population within the entire domain of convergence, to ensure the global computing ability of the algorithm, then taking advantage of the position of current flies to confirm the search direction and distance, so that the global computing ability of the algorithm can be confirmed. The improved algorithm is tested by two optimization function, the testing result shows that the algorithm has good global optimization ability. The successful application for the a-frame structure proves that the algorithm can be conducted to comprehensive promotion in the if eld of mechanical optimization design.