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Hybrid Algorithm Combining Ant Colony Optimization Algorithm with Genetic Algorithm

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3 Author(s)
Gao Shang ; Jiangsu Univ. of Sci. & Technol., Zhenjiang ; Jiang Xinzi ; Tang Kezong

By use of the properties of ant colony algorithm and genetic algorithm, a hybrid algorithm is proposed to solve the traveling salesman problems. First, it adopts genetic algorithm to give information pheromone to distribute. Second, it makes use of the ant colony algorithm to get several solutions through information pheromone accumulation and renewal. Finally, by using across and mutation operation of genetic algorithm, the effective solutions are obtained. Compare with the simulated annealing algorithm, the standard genetic algorithm, the standard ant colony algorithm, and statistics initial ant colony algorithm, all the 16 hybrid algorithms are proved effective. Especially the hybrid algorithm with across strategy B and mutation strategy B is a simple and effective better algorithm than others.

Published in:

Control Conference, 2007. CCC 2007. Chinese

Date of Conference:

July 26 2007-June 31 2007