摘要
Ant colony optimization algorithm is a novel simulated evolutionary algorithm, which provides a new method for complicated combinatorial optimization problems. In this paper the algorithm is used for solving the knapsack problem. It is improved in selection strategy and information modification, so that it can not easily run into the local optimum and can converge at the global optimum. The experiments show the robustness and the potential power of this kind of meta -heuristic algorithm.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Geoinformatics 2006 |
| 主期刊副标题 | Remotely Sensed Data and Information |
| DOI | |
| 出版状态 | 已出版 - 2006 |
| 已对外发布 | 是 |
| 活动 | Geoinformatics 2006: Remotely Sensed Data and Information - Wuhan, 中国 期限: 28 10月 2006 → 29 10月 2006 |
出版系列
| 姓名 | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| 卷 | 6419 |
| ISSN（印刷版） | 0277-786X |
会议
| 会议 | Geoinformatics 2006: Remotely Sensed Data and Information |
|---|---|
| 国家/地区 | 中国 |
| 市 | Wuhan |
| 时期 | 28/10/06 → 29/10/06 |
指纹
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Li, S., Wang, S., & Zhang, Q. (2006). An improved ant colony algorithm to solve knapsack problem. 在 Geoinformatics 2006: Remotely Sensed Data and Information 文章 64191T (Proceedings of SPIE - The International Society for Optical Engineering; 卷 6419). https://doi.org/10.1117/12.713269