混合算法在轻钢结构优化设计中的应用

Application of hybrid algorithm in optimization design of light steel structure

结合粒子群优化(PSO)算法快速的全局收敛性和蚁群优化(ACO)算法较强的寻优能力,提出了一种融合PSO算法和ACO算法的混合算法。首先利用PSO算法较强的全局搜索能力,产生各粒子的最优位置值;然后对ACO算法的蚂蚁总个数进行调整,在保证算法全局搜索能力的同时,避免陷入局部最优;最后利用改进的ACO算法对最优位置值做进一步优化。将该混合算法应用于轻钢结构优化设计中,建立优化设计模型。以轻钢门式框架为例,利用该模型进行优化分析,并与文献[11]中改进模拟退火算法的优化结果进行对比。结果表明,混合算法经过61次迭代后能够求出较好的全局最优解,合理可行。

Considering the rapid global convergence of the particle swarm optimization（PSO） algorithm and the strong optimization ability of the ant colony optimization（ACO） algorithm,the hybrid algorithm was put forward by combining with PSO algorithm and ACO algorithm.The optimal location values of the particles were generated by the strong global searching capability of the PSO algorithm.The total number of the ants was adjusted to ensure the global searching ability of the ACO algorithm and avoid trapping in local optimum.With the modified ACO algorithm,the optimal location values were further optimized.The hybrid algorithm is used to the optimization design of the light steel structure,and the design model was established.For an example,the wrap-round frame with light steel was optimized.By comparing to the optimization of the modified simulated annealing algorithm in literature the results showed that the hybrid algorithm which solved the global optimal solution after 61 iterations,was feasible,