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遗传算法是新近发展起来的一种模拟生命进化机制的搜索和优化方法。全局优化和隐含并行性使得遗传算法适合于大规模的复杂优化问题。在介绍遗传算法的基本概念和操作的基础上，提出了基于遗传算法的石油机械优化设计方法，以水力旋流器为例进行了计算并与常规优化方法进行了比较。两种优化方法的计算结果相差无几，但遗传算法是从多个初始点开始同时寻优，求解过程的收敛速度快，且获得的是全优解。水力旋流器的优化设计在经过２３代遗传之后已达到最优解，表明遗传算法具有较好的应用前景。
Genetic algorithm is a newly developed search and optimization method that simulates the evolution mechanism of life. Global optimization and implicit parallelism make the genetic algorithm suitable for large-scale complex optimization problems. Based on the introduction of the basic concepts and operation of genetic algorithm, a method based on genetic algorithm is proposed to optimize the design of petroleum machinery. The hydrocyclone is taken as an example and compared with the conventional optimization method. The results of the two optimization methods are almost the same, but the genetic algorithm starts from multiple initial points at the same time. The convergence speed of the solving process is fast and the whole optimal solution is obtained. The optimal design of the hydrocyclone has reached the optimal solution after 23 generations of genetic analysis, indicating that the genetic algorithm has a good application prospect.