中文摘要：

遗传算法是目前应用最广泛的优化算法，其最根本的优点是对非线性的适应性，特别适合于对非线性系统寻优，但是目前的各种遗传算法都存在速度慢的问题，对于实时性要求不高或者离线寻优是适用的，但是用于实时飞行器控制参数寻优，实时火控结算等任务，由于实时性要求高，因此目前的遗传算法就很难胜任。为了提高寻优算法的实时性，又要保持算法对非线性优化的适应性，提出一种类爬山快速搜索算法。并进行了理论证明和实例计算。理论分析和实践证明，该算法具有和遗传算法相似的收敛性，执行时间只有3s左右，而同样条件下普通遗传算法的执行时间则要50s左右。另外如果普通遗传算法的种群规模为n，则该算法的空间复杂性小于普通遗传算法空间复杂性的1／n，算法简单，易于编程实现。

英文摘要：

Genetic algorithm is widely used in optimization computations, it is characterized in high ability for non-linear system, so it is good at optimize for non-linear system. But all the variations of Genetic algorithm now have the same drawbacks of high time consumption, so it can be only used in offline optimization or some lower fast requirements applications. Due to it＇s slowly execution speed to find the optimal solutions, it can not be used for real timing optimization such as the real timing optimize the control parameters for the flying vehicles. In order to speed up the Genetic algorithm and keep the high ability for non-linear system of Genetic algorithm, presented a fast searching genetic algorithm based on a single chromosome, and verified the algorithm and testified the algorithm. The tests for the algorithm implies that this algorithm have the same convergence ability as the Genetic algorithm, and it only needs 3 seconds to find the optimal solutions compared with the 50 seconds required by the Genetic algorithm under the same conditions. In addition, if the size of the traditional genetic algorithm is n, then the memory requirements of this algorithm presented in this paper is 1/n compared with the memory requirements of traditional genetic algorithm, and it is simple and easy programming.