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Author:

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

Indexed by:

EI Scopus

Abstract:

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.

Keyword:

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

Author Community:

  • [ 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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Source :

Year: 2009

Page: 398-401

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 7

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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