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为提高工程结构优化的精度,应用了一种耦合惩罚函数的粒子群优化算法。该算法是从鸟群觅食活动中受到启发而得到的进化算法,其中以结构总重量为目标函数,以应力、位移和力为约束条件,研究粒子群参数变化对结果的影响。协调的参数组合可以避免陷入早熟收敛而能够快速获得全局的最优解。通过与ANSYS优化模块和其他方法的计算结果比较验证了该方法的有效性。
In order to improve the precision of engineering structure optimization, a particle swarm optimization algorithm coupled penalty function is applied. The algorithm is inspired by the foraging activities of bird flocks. The algorithm takes the total structure weight as the objective function and the stress, displacement and force as the constraint conditions to study the effect of particle swarm parameters on the results. The coordinated parameter combination can avoid getting stuck in premature convergence and can quickly obtain the global optimal solution. The effectiveness of this method is verified by comparing with the ANSYS optimization module and other methods.