中国邮电高校学报(英文) ›› 2008, Vol. 15 ›› Issue (4): 121-125.doi:

• Intelligent Computing • 上一篇    下一篇

Research on cultural algorithm for solving routing problem of mobile agent

马俊,ZHANG Jian-pei, YANG Jing, CHENG Li-li   

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
  • 收稿日期:2008-01-05 修回日期:1900-01-01 出版日期:2008-12-30
  • 通讯作者: 马俊

Research on cultural algorithm for solving routing problem of mobile agent

MA Jun, ZHANG Jian-pei, YANG Jing, CHENG Li-li   

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
  • Received:2008-01-05 Revised:1900-01-01 Online:2008-12-30
  • Contact: MA Jun

摘要:

The key idea behind cultural algorithm is to explicitly acquire problem-solving knowledge from the evolving population and in return apply that knowledge to guide the search. In this article, cultural algorithm-simulated annealing is proposed to solve the routing problem of mobile agent. The optimal individual is accepted to improve the belief space’s evolution of cultural algorithms by simulated annealing. The step size in search is used as situational knowledge to guide the search of optimal solution in the population space. Because of this feature, the search time is reduced. Experimental results show that the algorithm proposed in this article can ensure the quality of optimal solutions, and also has better convergence speed. The operation efficiency of the system is considerably improved.

关键词:

cultural;algorithm,;mobile;agent,;routing,;simulated;annealing

Abstract:

The key idea behind cultural algorithm is to explicitly acquire problem-solving knowledge from the evolving population and in return apply that knowledge to guide the search. In this article, cultural algorithm-simulated annealing is proposed to solve the routing problem of mobile agent. The optimal individual is accepted to improve the belief space’s evolution of cultural algorithms by simulated annealing. The step size in search is used as situational knowledge to guide the search of optimal solution in the population space. Because of this feature, the search time is reduced. Experimental results show that the algorithm proposed in this article can ensure the quality of optimal solutions, and also has better convergence speed. The operation efficiency of the system is considerably improved.

Key words:

cultural algorithm;mobile agent;routing;simulated annealing