@inproceedings{f76ea182c7e74cd3b0ea7590c9f93eb9,
title = "Hybrid ant colony algorithm based on scale compression",
abstract = "To improve performance of ant colony algorithm when solving large-scale TSP problem, a hybrid ant colony algorithm based on scale compression is proposed. First we use genetic algorithm to generate a suboptimal solution set and calculate their intersection. By eliminating all cities mapped by the elements among the intersection in the primal TSP problem, we convert the original problem into a new one with smaller scale. In addition, we design a new optimal state transition rule based on regional characteristic of optimal solutions to accelerate convergence speed. Simulation results show our approach possess high searching ability and excellent convergence performance.",
keywords = "Ant colony, Intersection, Scale compression, State transition rule, TSP",
author = "Yan, {Jian Feng} and Li, {N. A.} and Li, {Wei Hua} and Shi, {Hao Bin}",
year = "2007",
doi = "10.1109/ICMLC.2007.4370267",
language = "英语",
isbn = "142440973X",
series = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
pages = "885--889",
booktitle = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
note = "6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 ; Conference date: 19-08-2007 Through 22-08-2007",
}