基于改进NSGA-Ⅲ算法的动态武器协同火力分配方法

Method for Dynamic Weapon Coordinative Firepower Distribution Based on Improved NSGA-Ⅲ Algorithm

针对防御场景下的动态武器协同火力分配问题,将其转化为多目标约束组合优化问题,在考虑资源约束、可行性约束的前提下,以我方损失最小、消耗资源最小为原则,对敌方目标造成最大的伤害。基于此,在NSGA-Ⅲ算法的基础上提出基于A-NSGA-GKM算法的动态武器协同火力分配方法,通过遗传K均值聚类算法对初始参考点进行自动分组聚类,用聚类中心代替原参考点,引入基于惩罚的边界相交聚合函数代替原垂直距离,进一步提升原始算法的收敛性能,引入自适应机制保证优秀的解结构。最后,通过实验仿真表明所提优化算法具有较高的收敛性,该方法能够有效地解决动态武器协同火力分配优化问题。

Aiming at the problem of dynamic weapon coordinative firepower assignment in the defense scenario,it is transformed into multi-objective constrained combinatorial optimization problem.Under the premise of considering resource constraint and feasibility constraint,the principle is to cause maximum damage to enemy targets while with the cast of minimum loss and minimum consumption of resources on our side.Based on NSGA-Ⅲ algorithm,a new method for dynamic weapon coordinative firepower distribution based on A-NSGA-GKM algorithm has been proposed.The genetic K-means clustering algorithm is introduced to make automatic clustering of the initial reference points the cluster center is used to replace the original reference points the boundary intersecting aggregation function based on punishment is introduced to replace the original vertical distance,thereby the convergence performance of the original algorithm is further enhanced,the adaptive mechanism is introduced to ensure excellent solution structure.Finally,through experimental simulation,the results show that the proposed optimization algorithm has a higher convergence performance,and the proposed algorithm can solve the problem of dynamic weapon coordinative fire distribution effectively.