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舰艇编队防空火力基于改进遗传算法的分配方案
引用本文:韩瑞新,朱红胜,卢厚清,屈兵超,张宏军. 舰艇编队防空火力基于改进遗传算法的分配方案[J]. 解放军理工大学学报(自然科学版), 2006, 7(1): 46-50
作者姓名:韩瑞新  朱红胜  卢厚清  屈兵超  张宏军
作者单位:海军指挥学院,江苏,南京,210016;解放军理工大学,工程兵工程学院,江苏,南京,210007;解放军理工大学,工程兵工程学院,江苏,南京,210007
摘    要:描述了舰艇编队防空火力分配问题,建立了火力优化分配模型。结合舰艇编队防空作战的特点,分析了几种传统分配算法的不足。为了获得全局最优解,将遗传算法用于该火力分配优化研究中。针对标准遗传算法计算费时、稳定性差等不足,从初始群体均匀产生、适应度尺度变换、稳态繁殖、自适应遗传参数等方面作了改进,给出了基于改进遗传算法的模型求解方法和步骤。经过实例计算,取得了良好的分配效果,可为制定舰艇编队防空作战指挥自动化决策提供科学、有效的支持。

关 键 词:舰艇编队  防空  火力分配  遗传算法
文章编号:1009-3443(2006)01-0046-05
收稿时间:2005-08-27
修稿时间:2005-08-27

Optimized target assignment using improved genetic algorithmin naval fleet air defense
HAN Rui-xin,ZHU Hong-sheng,LU Hou-qing,QU Bing-chao and ZHANG Hong-jun. Optimized target assignment using improved genetic algorithmin naval fleet air defense[J]. Journal of PLA University of Science and Technology(Natural Science Edition), 2006, 7(1): 46-50
Authors:HAN Rui-xin  ZHU Hong-sheng  LU Hou-qing  QU Bing-chao  ZHANG Hong-jun
Affiliation:Naval Command College,Nanjing 210016,China;Engineering Institute of Corps of Engineers,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Engineering Institute of Corps of Engineers,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Engineering Institute of Corps of Engineers,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Engineering Institute of Corps of Engineers,PLA Univ.of Sci.& Tech.,Nanjing 210007,China;Engineering Institute of Corps of Engineers,PLA Univ.of Sci.& Tech.,Nanjing 210007,China
Abstract:Naval fleet air defense was studied and an anti air fire optimal target assignment model was established. Combining the features of naval fleet anti-air combat, several classical assignment algorithms were discussed. In order to find global optimal results efficiently, traditional GAs were improved and used for sloving the optimal allocation of naval fleet air defense. Though genetic algorithm, as an effective global search method, had been used widely, it had the disadvantages of slow convergence and poor stability in practical engineering. In order to overcome these problems, an improved genetic algorithm was proposed in terms of creation of the initial population, genetic operators, and etc. Finally, the steps to solve the optimal model were put forward. With this model, ideal results were obtained. This shows that the method can offer a scientific and effective support for a decision maker in command automation of the air defense combat.
Keywords:naval fleet   air defense   target assignment   genetic algorithm
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