| 引用本文: | 夏庆军,张安,张耀中.大规模编队空战队形优化算法[J].控制理论与应用,2010,27(10):1418~1422.[点击复制] |
| XIA Qing-jun,ZHANG An,ZHANG Yao-zhong.Formation-optimizing algorithm for large-scale air combat[J].Control Theory and Technology,2010,27(10):1418~1422.[点击复制] |
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| 大规模编队空战队形优化算法 |
| Formation-optimizing algorithm for large-scale air combat |
| 摘要点击 2075 全文点击 2711 投稿时间：2009-06-02 修订日期：2009-11-23 |
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| DOI编号 10.7641/j.issn.1000-8152.2010.10.CCTA090692 |
| 2010,27(10):1418-1422 |
| 中文关键词 队形优化 自适应遗传算法 市场机制 适应度函数 |
| 英文关键词 formation optimization adaptive genetic algorithms market mechanism fitness function |
| 基金项目 航空科学基金资助项目(20075153); 高校博士点基金资助项目(20060699026). |
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| 中文摘要 |
| 大规模编队队形优化是空战战术研究的一个重要方面, 但是对队形优化评估标准还没有建立一种有效的方法. 在利用市场机制完成目标分配的基础上, 提出使用编队目标函数作为队形优化评估标准. 为了验证该评估标准的有效性, 提出利用自适应遗传算法完成大规模编队协同空战队形优化. 首先采用层级方法对大规模飞机编队队形进行编码和解码, 然后利用编队目标函数构造出了适应度函数. 最后通过3组例子阐明了队形优化算法的有效性. |
| 英文摘要 |
| Formation optimization is an important tactic in large-scale air combats. However, there is no proper standard for evaluating the formation performance. A formation target function is proposed as the evaluation standard based on the market mechanism in target allocation. To verify the effectiveness of this evaluation standard, the adaptive genetic algorithm is applied to the formation optimization. Therein, the hierarchical structure method is used to encode and decode the formation in the large-scale air combat. Next, the fitness function is constructed by using the formation target function. Finally, the effectiveness of the formation optimization algorithm is illustrated by three scenarios. |