针对传统武器目标分配(WTA)方法中将目标视为相互独立实体的不足,提出一种适用于反坦克导弹武器目标分配的联合目标模型及利用自适应遗传算法对模型进行求解的思路,通过新的种群生成编码方法和单亲交叉与双亲交叉相结合的方法,缩小了可行解空间,克服了过早收敛,并加快了搜索速度。仿真表明了自适应遗传算法在求解反坦克导弹阵地WTA问题时不仅全局收敛性好,稳定性高,易于并行处理,且每个解都具有实际的可分配性。

Aiming at disadvantages of traditional weapon target assignment (WTA) methods which treat targets as mutually independent entities, an associated target model being the same with anti-tank missile target assignment was proposed. A combined algorithm based on self-adaptive genetic algorithm for solving weapon target assignment problem was presented. A new coding way of original swarm was established, which reduced the solution space. By introducing single ancestor chiasmatypy with double-single ancestor chiasmatypy, the inchoate convergent character was avoided with searching accelerated. Simulation results demonstrate that the algorithm can converge to the ideal steady state with high speed and provide practical solutions.