混合遗传算法及其在减载缓释机构中的应用
Soft Release Mechanism Optimization with Hybrid Genetic Algorithm

针对传统遗传算法早熟与收敛性差的问题,对遗传机制提出了改进策略,并与粒子群算法相混合,建立了一种混合遗传算法。该算法进一步被应用于火箭减载缓释机构的套筒外形优化问题。采用PATRAN的二次开发语言PCL对减载缓释机构进行参数化建模,通过对套筒的外形进行离散与优化,得到了满足Keepers提出的缓释特性的套筒外形。优化结果表明,混合遗传算法收敛速度较快,可行性高,有很好的工程适用性。
In order to overcome the shortage of prematurity and poor astringency of conventional genetic algorithms, a modified genetic algorithm strategy was proposed and mixed with particle swarm optimization to build a hybrid genetic algorithm. The algorithm was further applied to shape optimization of the sleeve of soft release mechanism. The parameteric model of the soft release mechanism was built by using the Patran Command Language. The sleeve shape was discretized and optimized, the sleeve shape with the soft release characteristics proposed by Keepers was achieved. The optimization result shows that the proposed hybrid genetic algorithms converges faster and has better feasibility compared with conventional genetic algorithms