Wuhan University Journal of Natural Sciences

, Volume 11, Issue 5, pp 1104–1108 | Cite as

A multi-agent approach for solving traveling salesman problem

  • Zhou Tiejun
  • Tan Yihong
  • Xing Lining
Web Information Mining and Retrieval


The traveling salesman problem (TSP) is a classical optimization problem and it is one of a class of NP-Problem. This paper presents a new method named multiagent approach based genetic algorithm and ant colony system to solve the TSP. Three kinds of agents with different function were designed in the multi-agent architecture proposed by this paper. The first kind of agent is ant colony optimization agent and its function is generating the new solution continuously. The second kind of agent is selection agent, crossover agent and mutation agent, their function is optimizing the current solutions group. The third kind of agent is fast local searching agent and its function is optimizing the best solution from the beginning of the trial. At the end of this paper, the experimental results have shown that the proposed hybrid approach has good performance with respect to the quality of solution and the speed of computation.

Key words

traveling salesman problem multi-agent approach genetic algorithm ant colony system 

CLC number

TP 18 


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Copyright information

© Springer 2006

Authors and Affiliations

  1. 1.School of Computer and CommunicationHunan UniversityChangsha, HunanChina
  2. 2.Department of Information and Computer ScienceChangsha UniversityChangsha, HunanChina
  3. 3.School of ManagementNational University of Defense TechnologyChangsha, HunanChina

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