@inproceedings{53ac3a76c57f49b1aaf4688667e4fcd7,
title = "A fast particle swarm optimization algorithm with cauchy mutation and natural selection strategy",
abstract = "The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group's previous best to optimize problems. One problem exists in PSO is its tendency of trapping into local optima. In this paper, a fast particle swarm optimization (FPSO) algorithm is proposed by combining PSO and the Cauchy mutation and an evolutionary selection strategy. The idea is to introduce the Cauchy mutation into PSO in the hope of preventing PSO from trapping into a local optimum through long jumps made by the Cauchy mutation. FPSO has been compared with another improved PSO called AMPSO [12] on a set of benchmark functions. The results show that FPSO is much faster than AMPSO on all the test functions.",
keywords = "Cauchy mutation, Particle swarm optimization, Swarm intelligence",
author = "Changhe Li and Yong Liu and Aimin Zhou and Lishan Kang and Hui Wang",
year = "2007",
doi = "10.1007/978-3-540-74581-5\_37",
language = "英语",
isbn = "9783540745808",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "334--343",
booktitle = "Advances in Computation and Intelligence - Second International Symposium, ISICA 2007, Proceedings",
address = "德国",
note = "2nd International Symposium on Intelligence Computation and Applications, ISICA 2007 ; Conference date: 21-09-2007 Through 23-09-2007",
}