系统工程与电子技术 ›› 2018, Vol. 40 ›› Issue (10): 2242-2248.doi: 10.3969/j.issn.1001-506X.2018.10.13

• 系统工程 • 上一篇    下一篇

海上多舰协同防空部署优化研究

杨毅, 南英   

  1. 南京航空航天大学航天学院, 江苏 南京 210016
  • 出版日期:2018-09-25 发布日期:2018-10-10

Cooperative deployment optimization of multi-warship for air defense

YANG Yi, NAN Ying   

  1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Online:2018-09-25 Published:2018-10-10

摘要: 针对海上多舰协同防空部署优化问题,在已知敌方进攻态势和我方防御能力的条件下,综合分析各项影响攻防效果的因素,结合不可逃逸区,综合设计了多舰协同防空部署的性能指标。本文给出了多弹群体进攻下海上多舰协同防空部署的问题描述,并采用了共生有机搜索算法(symbiosis organisms search,SOS)对该问题进行优化求解得出最优部署方案。共生有机搜索算法通过模拟共生、共栖和寄生3种生物间的生存关系对协同防空部署的问题进行优化,在该类具有约束的非线性优化问题中,SOS算法相较于粒子群算法不易陷入局部最优,能够求解得到更优解,收敛速度相比提高近10%。在想定假设条件下,通过数值仿真计算结果对所提出的模型和算法进行了合理性和有效性分析,表明该部署优化方法得到的方案是正确可行的。

Abstract: This paper presents comprehensive performance index of multi-warship deployment for air defense, after analyzing various factors of incoming target and warship, which would affect the effectiveness of interception. This paper provides the formulation of the multiwarship cooperative deployment problem, and optimizes the cooperative deployment optimization problem of multiwarship by using the symbiosis organisms search (SOS) algorithm. The SOS algorithm optimizes the cooperative deployment optimization problem by simulating the mutualism phase, commensalism phase, and parasitism phase. Comparing to particle swarm optimization (PSO), SOS can obtain better solution with higher convergence rate. Numerical simulation results are provided to support the method in rationality. Compared with the PSO algorithm, the SOS algorithm performs better in this problem.