基于合作协同进化的多机空战目标分配

为寻找一种满足多机空战需求的目标分配优化方法,提升空战效能,提出了一种基于合作协同进化的多机空战目标分配方法。首先，该方法基于单机空战优势,建立多机协同空战优势评价指标体系。然后,对战机间的协同相关性进行分析计算,建立多机协同空战目标分配模型。在变长度染色体遗传算法(genetic algorithm, GA)的基础上,设计了基于交叉、嫁接、分裂和拼接算子的改进合作协同进化算法,提高了模型的进化效率。最后，设计实验分别对优势评价指标体系的有效性、静态算例、动态算例和大规模无人战斗机算例进行仿真验证,并将2种模型以及4种算法的计算结果和所提算法的实验结果进行对比。仿真结果表明，改进合作协同进化算法适用于该模型计算,结果收敛稳定,亲和度值显著提升,能够优化目标分配方案,在空战中具有一定的应用意义。

Multi-aircraft air combat target allocation based on cooperative co-evolutionary

In order to find an optimal target allocation method to meet the requirements of multi-aircraft air combat and improve the air combat efficiency, a multi-aircraft air combat target allocation method based on cooperative co-evolutionary is proposed. Firstly, this method establishes a multi-aircraft cooperative air combat superiority evaluation index system based on single-aircraft air combat superiority. Secondly, the cooperative correlation between aircraft is analyzed and calculated, and a multi-aircraft cooperative air combat target allocation model is established. On the basis of variable length chromosome genetic algorithm(GA), an improved cooperative co-evolutionary algorithm based on crossover, grafting, splitting and splicing operators is designed, which improves the evolution efficiency of the model. Finally, experiments are designed to validate the effectiveness of the superiority evaluation index system, static examples, dynamic examples and large-scale unmanned combat aerial vehicles (UCAV) examples. The results of the two models and four algorithms are compared with the experimental results. The simulation results show that the improved cooperative co-evolutionary algorithm is suitable for the calculation of this model. The convergence is stable and the affinity value is significantly improved. So the target allocation scheme can be optimized and it has certain application significance in air combat.