基于云遗传算法的防空火力分配

doi:10.16182/j.issn1004731x.joss.201809038

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (9): 3533-3537.doi: 10.16182/j.issn1004731x.joss.201809038

基于云遗传算法的防空火力分配

雷鸣^1,2, 谢斌^1,2

1.中国电子科技集团公司第二十八研究所,江苏南京 210007;
2.信息系统工程重点实验室,江苏南京 210007

收稿日期:2016-06-20 出版日期:2018-09-10 发布日期:2019-01-08
作者简介:雷鸣(1984-),男,山西,硕士,高工,研究方向为机器学习算法、优化算法设计、复杂系统建模与仿真等;谢斌(1979-),男,湖北,本科,高工,研究方向为系统仿真、软件架构与设计。

Air Defense Fire Distribution Based on Cloud-genetic Algorithm

Lei Ming^1,2, Xie Bin^1,2

1.The 28th Research Institute of China Electronic Group Corporation, Nanjing 210007, China;
2. Science and Technology on Information Systems Engineering Laboratory, Nanjing 210007, China

Received:2016-06-20 Online:2018-09-10 Published:2019-01-08

摘要/Abstract

摘要： 防空火力分配问题是研究防空作战中的一个重要问题,对战争胜负有重要的作用。针对防空战争的特点,建立了以打击效益最大为优化目标的火力分配模型,基于云模型的优良特性,结合遗传算法,提出了一种基于云模型的改进遗传算法,主要是对交叉变异算子进行了构造,不仅能加快收敛速度,提高了算法的搜索效率,还能较好地避免算法陷入局部最优和早熟收敛。通过对某防区火力防空问题的仿真实验,验证了算法的可行性。

关键词: 火力分配, 云模型, 云发生器, 云遗传算法

Abstract: Air defense fire distribution is a critical problem in the researches on air defense operation. This paper builds a fire distribution model with the maximization of strike as its optimization objective, and proposes a cloud model-based modified genetic algorithm based on the advantageous characteristics of cloud model in combination of genetic algorithm, which not only accelerates the rate of convergence and increases search efficiency of the original algorithm, but also preferably avoids the problems of local optimum and premature convergence. Simulation experiments have verified the feasibility of the modified algorithm.

Key words: fire distribution, cloud model, cloud generator, cloud-genetic algorithm

中图分类号:

TP391

雷鸣, 谢斌. 基于云遗传算法的防空火力分配[J]. 系统仿真学报, 2018, 30(9): 3533-3537.

Lei Ming, Xie Bin. Air Defense Fire Distribution Based on Cloud-genetic Algorithm[J]. Journal of System Simulation, 2018, 30(9): 3533-3537.

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基于云遗传算法的防空火力分配

Air Defense Fire Distribution Based on Cloud-genetic Algorithm

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