摘要
In order to overcome the standard particle swarm optimization algorithm which is easily trapped in local minima and optimize the shortcoming of low precision, this paper proposed a way which can make multiple information exchange between particles come true: the multiple population co-evolution PSO algorithm. This paper proposes a multiple population co-evolutionary algorithm to achieve communication among populations, and then show the feasibility and effectiveness of this algorithm through experiments.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Advances in Swarm Intelligence - 5th International Conference, ICSI 2014, Proceedings |
| 编辑 | Ying Tan, Yuhui Shi, Carlos A. Coello Coello |
| 出版商 | Springer Verlag |
| 页 | 434-441 |
| 页数 | 8 |
| ISBN（电子版） | 9783319118963 |
| DOI | |
| 出版状态 | 已出版 - 2014 |
| 活动 | 5th International Conference on Advances in Swarm Intelligence, ICSI 2014 - Hefei, 中国 期限: 17 10月 2014 → 20 10月 2014 |
出版系列
| 姓名 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| 卷 | 8795 |
| ISSN（印刷版） | 0302-9743 |
| ISSN（电子版） | 1611-3349 |
会议
| 会议 | 5th International Conference on Advances in Swarm Intelligence, ICSI 2014 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Hefei |
| 时期 | 17/10/14 → 20/10/14 |
指纹
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Xiao, X., & Zhang, Q. (2014). The multiple population co-evolution PSO algorithm. 在 Y. Tan, Y. Shi, & C. A. C. Coello (编辑), Advances in Swarm Intelligence - 5th International Conference, ICSI 2014, Proceedings (页码 434-441). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 8795). Springer Verlag. https://doi.org/10.1007/978-3-319-11897-0_49