[1]YIN Feng,WANG Yao-nan,LIU Wei,et al.Design and simulation of an ant colony algorithm based on individual velocity differences[J].CAAI Transactions on Intelligent Systems,2009,4(6):528-533.[doi:10.3969/j.issn.1673-4785.2009.06.010]
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Design and simulation of an ant colony algorithm based on individual velocity differences

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 6 Page number: 528-533 Column: 学术论文—智能系统 Public date: 2009-12-25
Title:
Design and simulation of an ant colony algorithm based on individual velocity differences
Author(s):
YIN Feng1;  WANG Yao-nan1;  LIU Wei2;  ZHOU Liang1
1. College of Electrical and Information Engineering of Hunan University, Changsha 410082, China; 2. School of Software, Hunan Vocational College of Science and Technology, Changsha 410118,China
Keywords:
ant colony algorithm;  TSP;  pheromone;  NP-hard
CLC:
TP301.6
DOI:
10.3969/j.issn.1673-4785.2009.06.010
Abstract:
A new implementation of the ant colony optimization (ACO) algorithm was primarily focused on improving search speed and preventing stagnation. To resolve these two issues, improvements based on velocity were proposed, producing a VACO algorithm. By constructing a time-function for local paths and ant velocity, and building a dynamic release mechanism for pheromones in the time-function, it accelerated positive feedback from the accumulation of pheromones, leading to better paths and improved convergence speed. A strategy of continuous inter-cell mutation sped up local searches and at the same time effectively prevented the algorithm being trapped in local optimums. The results showed that the proposed algorithm improves convergence and increases the possibility of finding optimal solutions.
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