基于遗传算法的燃气涡轮发动机循环优化

遗传算法（Genetic Algorithms简写GA）是用于优化问题的新的有用的工具，其运用了自然界中的法则并且在可能的解空间上形成多点逼近的评价工具。遗传算法的特性使他能够有效的运用在发动机的设计工作中。论文的工作就是得出了基于要遗传算法的燃气涡轮发动机循环的优化。论文分为几个不同的部分，首先是关于GA的概要描述和主要架构。（初始群体的建成、每个个体的适应值评价、发展新一带的标准：成员的选择、繁殖、变异等等），其次是用GA的应用程序优化燃起涡轮发动机循环和相关问题，文章最后介绍了单目标和多目标发动机循环优化的例子。

Genetic algorithms for the optimization of gas turbine cycles

Genetic Algorithms are new techniques useful for optimization problems. They work in the same way of Nature and they are multi approach tools evaluating the space of probable solutions of a problem. For their characteristics GA may be effectively employed for many activities during engine design. This paper presents the results of a study carried out for optimizing the cycles of gas turbine engines. The problems involved by the GA technique and dealing with the different steps of optimization are constraints.