@inproceedings{3a8d22aa838944028e884bb10342a003,
title = "ACO with fuzzy pheromone laying mechanism",
abstract = "Pheromone laying mechanism is an important aspect to affect performance of ant colony optimization (ACO) algorithms. In most existing ACO algorithms, either only one best ant is allowed to release pheromone, or all the ants are allowed to lay pheromone in the same way. To make full use of ants to explore high quality routes, a fuzzy pheromone laying mechanism is proposed in the paper. The amount of ants that are allowed to lay pheromone varies at each iteration to differentiate different contributions of the ants. The experimental results show that the proposed algorithm possesses high searching ability and excellent convergence performance in comparison with the classic ACO algorithm.",
keywords = "ant colony optimization (ACO), fuzzy, pheromone laying",
author = "Liu Yu and Yan, \{Jian Feng\} and Yan, \{Guang Rong\} and Lei Yi",
year = "2012",
doi = "10.1007/978-3-642-31837-5\_16",
language = "英语",
isbn = "9783642318368",
series = "Communications in Computer and Information Science",
pages = "109--117",
booktitle = "Emerging Intelligent Computing Technology and Applications - 8th International Conference, ICIC 2012, Proceedings",
note = "8th International Conference on Emerging Intelligent Computing Technology and Applications, ICIC 2012 ; Conference date: 25-07-2012 Through 29-07-2012",
}