基于整数域改进粒子群优化算法的多平台武器目标分配

Weapon-target Assignment in Multi-launcher System Based on Improved Integer Field Particle Swarm Optimization Algorithm

武器—目标分配(WTA)问题是军事运筹学中经典的NP完全问题,其模型为非线性整数规划模型,包含多种约束条件,求解复杂、收敛速度慢,采用改进粒子群优化(PSO)算法求解WTA问题。在建立WTA最优化分配模型的基础上,提出了一种针对多约束WTA问题的粒子编码方案及模型的适应度函数,解决了粒子的整数域初始化问题。采用粒子相似度函数,重新定义PSO算法中速度及距离概念,进而提出一种适用于整数规划的粒子速度更新算法及粒子寻优调整操作方案,提高了PSO算法的迭代效率及寻优能力。仿真结果表明,该算法计算快速有效,特别适合粒子群体规模较大时的WTA问题实时求解。

Weapon-target assignment（WTA） is a classic hard NP problem in military operation research,as its nonlinear integer programming model includes a variety of constraints,and its solution is complex and time-consuming.An improved particle swarm optimization algorithm was used to solve WTA problem.First,a particle decoding scheme and a sufficiency function were proposed for WTA optimization assignment model to solve the problem of integer field initialization.Then,a particle similarity function was used to redefine the velocity and distance concepts in the algorithm.A particle velocity update method and a particle optimization adjust operation plan were proposed to improve the iterative efficiency and optimization ability.Simulation results show that the algorithm is quick and effective,especially for solving real-time WTA problem with large particle group.