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作者:

Dai, Qiguo (Dai, Qiguo.) | Ji, Junzhong (Ji, Junzhong.) (学者:冀俊忠) | Liu, Chunnian (Liu, Chunnian.)

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摘要:

Aiming at the poor performance of convergence of ant colony optimization (ACO), in this paper, a novel pheromone initialization strategy of ACO for the traveling salesman problem (TSP) is put forward. More precisely, the pheromone matrix of a specific ACO algorithm is initialized by the minimal spanning tree (MST) information. Simulation results demonstrate that the proposed strategy could improve the convergence performance of ACO both in term of quality of solution and speed of convergence. ©2009 IEEE.

关键词:

Ant colony optimization Artificial intelligence Biomimetics Computation theory Traveling salesman problem Trees (mathematics)

作者机构:

  • [ 1 ] [Dai, Qiguo]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Ji, Junzhong]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Liu, Chunnian]Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, 100124, China

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年份: 2009

页码: 398-401

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 6

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