This paper extends an optimization procedure to obtain the optimal dynamic properties of laminated sandwich multiphase nanocomposite truncated conical shell under magneto-hygro-thermal conditions. Based on principle of Hamilton, the equations of motion are obtained and solved by differential quadrature method and Bolotin's methods for obtaining the dynamic stability region. Based on particle swarm optimization and harmony search algorithms, a novel hybrid optimization method basis HS and PSO is proposed to enhance the performance and convergence of optimum dynamic conditions in this problem. By applying the hybrid optimization algorithm namely as HS-PSO, the volume percent of CNT and carbon fiber, number of laminas, cone semi vertex angle and moisture changes are optimized and the effects of magnetic field and temperature are shown on the dynamic stability of system. The result illustrates that proposed PSO-HS method with same conditions by other optimization methods as harmony memory size (number of particles) of 5 and total iterations of 100 shows the superior convergence performance compare to HS and PSO algorithms.

本文扩展了一个优化程序，以获得在磁-湿-热条件下层压夹层多相纳米复合材料截锥壳的最佳动态性能。根据Hamilton原理，利用微分求积法和Bolotin法求取动态稳定域，得到并求解运动方程。基于粒子群优化和和声搜索算法，提出了一种基于HS和PSO的新型混合优化方法，以提高该问题最优动态条件的性能和收敛性。通过应用混合优化算法，即 HS-PSO，CNT 和碳纤维的体积百分比，层数，对圆锥半顶角和水分变化进行了优化，并显示了磁场和温度对系统动态稳定性的影响。结果表明，与HS和PSO算法相比，所提出的PSO-HS方法在与其他优化方法相同的条件下，和谐记忆大小（粒子数）为5，总迭代次数为100次，显示出优越的收敛性能。