摘要
提出一种高效率的基于MPI(Message Passing Interface)环境的并行混沌遗传算法,求解反导预警场景下的雷达部署优化问题,实现对弹道导弹从被发现到连续跟踪的早期预警。利用分布式并行计算的思想,代替传统串行计算,使算法效率提高7-8倍;为了避免出现"早熟"现象,引入混沌序列对某一代群体中的个体加混沌扰动来提高种群的多样性,并给出了并行计算的混沌遗传算法处理流程。仿真实例表明该算法能够快速得出优化部署方案,时间复杂度降低,大大提高了算法效率,对反导预警雷达部署有较大的应用价值。
In view of the disposition of radar detection under anti-missile warning,a high efficiency parallel chaos genetic algorithm based on MPI environment is proposed to achieve early warning for ballistic missile. Traditional serial computing is instead of the distributed parallel computing ideas,which greatly improves the efficiency of operations. The up-time of new algorithm is shortened 70%- 80%. To avoid premature,we introduce chaotic sequence to disturb a generation population which increased population diversity. The flow of chaos GA based on parallel computing is described in the paper. Simulation results show that the new algorithm can obtain the best disposition scheme faster. Its performance is superior to the traditional genetic algorithm and greatly improves the efficiency. The algorithm in this paper is important to anti-missile warning radar disposition.
出处
《中国电子科学研究院学报》
北大核心
2016年第3期276-282,共7页
Journal of China Academy of Electronics and Information Technology
关键词
反导预警雷达
优化部署
混沌
遗传算法
并行计算
anti-missile warning radar
disposition optimization
Chaos
GA
Parallel Computing