吉林大学学报(理学版) ›› 2018, Vol. 56 ›› Issue (5): 1219-1223.

• 计算机科学 • 上一篇    下一篇

基于CW节约算法和遗传算法的网络优化

张赛男1, 刘东亮2   

  1. 1. 吉林财经大学 新闻与传播学院, 长春 130117; 2. 东北师范大学 信息科学与技术学院, 长春 130117

  • 收稿日期:2018-02-26 出版日期:2018-09-26 发布日期:2018-11-22
  • 通讯作者: 张赛男 E-mail:sainan@163.com

Network Optimization Based on CW Saving Algorithm and Genetic Algorithm#br#

ZHANG Sainan1, LIU Dongliang2   

  1. 1. School of Journalism and Communication, Jilin University of Finance and Economics, Changchun 130117, China;2. School of Information Science and Technology, Northeast Normal University, Changchun 130117, China

  • Received:2018-02-26 Online:2018-09-26 Published:2018-11-22

摘要: 将节约算法和遗传算法相结合解决通信网络规划的优化问题, 该方法融合了节约算法的快速收敛特点, 通过遗传算法可全面考虑通信网络的各种设计成本和实际通信限制问题. 实验结果表明, 该算法相对于传统的贪婪算法或最小生成树法, 有更快的运算速度和更好的可行解.

关键词: 网络优化, 遗传算法, 节约算法, 通信

Abstract: We combined the saving algorithm with the genetic algorithm to solve the optimization problem of communication network planning. The algorithm integrated the fast convergence characteristics of the saving algorithm, and the various design cost and practical communication restrictions of the communication network can be fully considered through the genetic algorithm. The experimental results show that, compared with the traditional greedy algorithms or minimum spanning tree methods, the algorithm has higher computing speed and better feasible solutions.

Key words: network optimization, genetic algorithm, saving algorithm, communication

中图分类号: 

  • TP391