基于改进天鹰优化器的抱杆结构优化

Structure Optimization of Holding Pole Based on Improved Aquila Optimizer

为了提高抱杆设计的安全性和经济性,提出一种基于改进天鹰优化器的抱杆结构优化方法。根据抱杆工程实例,建立轻量化设计模型。将角钢杆件的截面尺寸作为优化变量,采用罚函数法处理许用应力、位移和屈曲系数三种约束条件。为了解决天鹰优化器局部搜索能力不足的问题,使用混沌映射进行种群初始化,使首代种群在搜索空间内分布更加均匀,并引入新的平衡方式使算法在迭代后期仍具有全局搜索能力,同时加入非线性参数增强局部搜索能力,引入反向学习策略增强算法摆脱局部最优的能力。十杆平面桁架结构尺寸优化算例结果验证了改进算法具有更好的寻优能力。抱杆结构轻量化设计结果表明,改进的天鹰优化器提供的设计方案更佳,抱杆质量减轻了16.55%。改进天鹰优化器能够有效处理平面桁架和空间杆系结构的优化设计问题。

In order to improve the safety and economy of the holding pole design,an optimization method of the holding pole structure based on the improved aquila optimizer(IAO)was proposed.The lightweight design model was established according to the engineering project of the holding pole.The optimization variables were the section sizes of the angle steels,and the penalty function method was used to deal with the three constraints of allowable stress,displacement and buckling coefficient.In order to solve the problem of insufficient local search ability of the aquila optimizer,the IAO used chaotic map for population initialization to make the first generation population more evenly distribute in the search space,introduced a new balance method to make the algorithm still have the global search ability in the late iteration,added nonlinear parameter to enhance the local search ability,and applied opposition-based learning strategy to enhance the ability of the algorithm to get rid of local optima.The size optimization results of the ten-bar plane truss structure verify that the IAO has better search ability.And the results of the lightweight design of the holding pole show that IAO provides a better design scheme with 16.55%reduction in mass.The IAO can effectively deal with the optimization design problems of plane truss and space bar system structure.