As the two main global optimization algorithms, genetic algorithm and simulated annealing algorithm have their own advantages and disadvantages in global search and local search. Combining the genetic algorithm with simulated annealing algorithm, this paper improves the airfoil optimization design based on the existing adaptive simulated annealing genetic algorithm. It proposes a random neighborhood expansion mechanism and adds this mechanism to the simulated annealing process. An improved adaptive simulated annealing genetic algorithm is formed. The improved adaptive simulated annealing genetic algorithm can improve the optimization efficiency of the algorithm and make it look for better results in the same time. Finally, an example of optimization design of NACA4418 is used to verify the optimization efficiency of the algorithm, and the feasibility of the algorithm in the optimal design of the airfoil is proved.%遗传算法与模拟退火算法作为目前两种主要的全局寻优算法,在全局搜索与局部搜索方面有着各自的优缺点.文章结合遗传算法与模拟退火算法,在已有自适应模拟退火遗传算法的基础上,针对风力机翼型优化设计做出改进,提出一种邻域随机拓展机制,在模拟退火环节加入该机制,形成改进的自适应模拟退火遗传算法.改进的自适应模拟退火遗传算法能够提高算法优化效率,使其在相同时间内寻找到更为优质的结果.最后,给出对翼型NACA4418进行优化设计的计算实例,验证了该算法的优化效率,证明了该算法在风力机翼型优化设计中的可行性.
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