基于自适应遗传算法的逐次超松驰迭代法

Successive Over-Relaxation Based on Adaptive Genetic Algorithm

确定逐次超松驰迭代法中的最佳松驰因子,迄今,人们还没有给出一可行实用的方法.利用自适应遗传算法全局搜索性能、并行性及其遗传操作,构造出近似确定最佳松驰因子的一种自适应进化方法,并由此得到一近似确定ω功能的自适应逐次超松驰迭代算法.数值算例表明,该算法在求解线性方程组中是可行的,实用和快捷的.

So far, there is not any doable applied method for determining the best relaxation factor of Successive Over Relaxation. In this paper, based on the global search, parallel and genetic operation of adaptive genetic algorithm, an adaptive evolution method is set up for determining the best relaxation factor. An adaptive successive over relaxation iterative method using this new algorithm is feasible, practical and speedy for solving the linear systems.