区间不确定性下的空中作战行动过程优选方法

针对空中作战行动过程（COA）设计问题，根据动态影响网（DINs）理论和改进快速非支配排序遗传（NSGA-Ⅱ）算法，提出一种基于DINs和区间多目标优化的空中作战过程优选方法。首先，分析空中作战过程基本概念，分别进行静态和动态建模，并对参数不确定性进行分析。然后，基于改进Kendall协和系数检验法确定一致性检验后的关键参数，设计DINs概率传播算法。随后，分析期望效果实现概率与各关键参数的相关关系，在分析行动过程优选效果评价指标基础上，采用改进NSGA-Ⅱ算法对模型进行求解。最后，通过多组仿真案例，验证了模型的合理性，以及算法的有效性和优越性。

Optimized selection method for air combat course of action with interval uncertainty

This paper proposes an optimized selection method for the design of air combat Course of Action (COA) based on Dynamic Influence Nets (DINs) and interval multi-objective optimization according to the theory of DINs and the improved Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ). We first analyzed the basic concepts of air combat COA, established the static and dynamic models separately, and performed a detailed analysis of parameter uncertainty. Then, based on the improved Kendall concordance test method, we determined the key parameters after the consistency test, and designed the DINs probability propagation algorithm. Subsequently, the correlation between the realization probability of desired effects and each key parameter was analyzed, and the improved NSGA-Ⅱ algorithm was used to solve the model after the analysis of the effect evaluation index of COA optimization. Finally, through multiple sets of simulation cases, the rationality of the model and the effectiveness and superiority of the algorithm were verified.