一种基于遗传粒子群混合的路由优化算法  

A Routing Optimization Algorithm Based on the Hybrid of GA and PSO

作　　者：王娜娜[1] Wang Na-na(School of Mechanical and Electrical Engineering,Zhengzhou Vocational University of Information and Technology,Henan Zhengzhou 450046)

机构地区：[1]郑州信息科技职业学院机电工程学院,河南郑州450046

出　　处：《电子质量》2017年第5期1-4,14,共5页Electronics Quality

基　　金：河南省教育厅高等学校重点科研项目(15B413007)

摘　　要：传统的基于最短路径的路由算法不能合理利用现有网络,容易造成网络拥塞。该文基于粒子群算法和遗传算法的核心思想,将两种算法融合起来,提出一种基于遗传粒子群混合算法的路由优化算法,用来求解多Qo S约束的路由问题,算法以改进的粒子群算法为主线,并引入遗传算法的变异思想避免算法陷入局部最优。在满足带宽、费用以及时延约束的基础上,将网络负载的均衡性和网络资源消耗作为优化目标,达到优化路径选择,避免网络拥塞的目的。仿真结果表明该算法的可行性和有效性。The traditional routing algorithm based on the Shortest Path First cannot make use of the existing network,which may lead to network congestion.Based on the idea of Particle Swarm Optimization and Genetic Algorithm,this paper proposes a routing optimization algorithm based on the hybrid of GA and PSO,which is used to solve the problem of multiple QoS constrained routing problem.The algorithm use the PSO as the main line,and introduce the mutation method to avoid the local optimum.Based on the satisfaction of bandwidth,cost and delay constrains,the network resource consumption and load balancing are taken as the optimization objective,which can achieve the optimal routing and avoid the network congestion.Simulation results show the feasibility and effectiveness of the proposed algorithm.

关 键 词：遗传粒子群混合算法 路由优化 QOS 负载均衡 网络拥塞 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]