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Author:

Ji, Jun-Zhong (Ji, Jun-Zhong.) (Scholars:冀俊忠) | Huang, Zhen (Huang, Zhen.) | Liu, Chun-Nian (Liu, Chun-Nian.)

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EI Scopus PKU CSCD

Abstract:

To improve the computation performance of Ant Colony System for solving large scale Traveling Salesman Problems (TSP), a new algorithm is presented in this paper. It adopts a set of multistage strategies to look for an optimal solution. The analysis for computation complexity and experimental results for TSP problems demonstrate that the proposed algorithm can greatly improve the speed of convergence while keeping more optimal solutions.

Keyword:

Traveling salesman problem Computational complexity Optimization Clustering algorithms

Author Community:

  • [ 1 ] [Ji, Jun-Zhong]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Huang, Zhen]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Liu, Chun-Nian]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2008

Issue: 4

Volume: 34

Page: 434-440

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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