计算机网络中路由选择的优化研究

为了改进计算机网络的性能 ,提出了一种改进的并行遗传算法 ,采用多群体并行进化与自适应地改变遗传参数 ,对计算机网络中路由选择问题进行了优化 ,比较了不同算法所得到的链路利用率及网络的平均时延 .计算机仿真实验结果表明 ,该算法能较迅速地求出全局近似最优解 ,并且与传统的方法相比较 ,解的质量能大幅度地提高 ,证明此改进的并行遗传算法是行之有效的

Optimizations of route selection and capacity and flow assignments in computer networks

In order to improve performances of computer networks, an improved parallel genetic algorithm is presented. The parallel evolution of many groups and self adaptive changing the genetic parameters are used. The problem of route selection in computer networks is optimized. The utilization rates of links and the average delays of networks obtained by using different algorithms are compared. The outcomes of computer simulation experiments are shown that, the near overall optimal solution by using the algorithm can be more rapidly solved, and the quality of solution can be greatly improved in comparison with the traditional method. And it proves that the improved parallel genetic algorithm is effectual.