A study about the improvement of Ant colony algorithm

DOI

10.2991/nceece-15.2016.120How to use a DOI?

Keywords

ant colony algorithm; genetic algorithm; crossover operation

Abstract

The ant colony algorithm is a new kind of simulated evolutionary algorithm for random searching, which converges to the optimal path by the accumulation of pheromone and updating. But it lacks the global searching ability, and easily falls into local minimum and appears the phenomenon of premature stagnation. In this paper, the improved method, which applies a stronger global searching ability of genetic algorithm and introduces the improved crossover and mutation operation, is designed to enhance the global searching ability of ant colony algorithm. The improved algorithm is applied to a two-dimensional function optimization simulation calculation. The results show that the improved ant colony algorithm is better than the original in accuracy and time efficiency

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wen-zhe Liang
AU  - Qing-yin Niu
AU  - Chao Fan
PY  - 2015/12
DA  - 2015/12
TI  - A study about the improvement of Ant colony algorithm
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 648
EP  - 651
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.120
DO  - 10.2991/nceece-15.2016.120
ID  - Liang2015/12
ER  -