基于遗传算法的优化函数Python实现

Python Implementation of Optimization Function Based on Genetic Algorithm

传统的遗传算法解决了搜索算法中计算量大的问题,但也存在不能自动优化函数和全局收敛差等问题。自适应遗传算法是一种改进的遗传算法,它在传统遗传算法的基础上引入了一些自适应性机制,以提高算法的性能和适用性。文章以求解心电图和航空轨迹函数最优解为例,使用Python编程证实自适应算法在实际应用中具有更好的性能和适用性。

Traditional genetic algorithms have solved the problem of high computational complexity in search algorithms,but there are also problems such as inability to automatically optimize functions and poor global convergence.Adaptive genetic algorithm is an improved genetic algorithm that introduces some adaptive mechanisms based on the traditional genetic algorithm to improve the algorithm's performance and applicability.The article takes solving the optimal solution of electrocardiogram and aviation trajectory function as examples,and uses Python programming to demonstrate that the adaptive algorithm has better performance and applicability in practical applications.