研究了多机协同多目标攻击空战决策问题。它是依据空战形势，寻求M架友机对N架敌机的一个适当的攻击分配方案，以实现最优的期望攻击效果。为此，本文首先建立了决策问题的数学模型，接着应用混合自适应遗传算法对其进行求解。在混合自适应遗传算法中，将一种局部搜索方法引入自适应遗传算法以提高其搜索能力。同时，设计了用于满足决策问题的非常规交叉算子。仿真实验结果表明所设计的混合自适应遗传算法比自适应遗传算法能更有效的解决协同多目标攻击空战决策问题。

The Decision-Making (DM) problem is investigated for Cooperative Multiple Target Attack in air combat. It is to find a proper assignment of M friendly fighters to N hostile fighters in order to achieve the optimal expected attack effect according to the air combat situation. In this paper, the DM problem is formulated mathematically and then a Hybrid Adaptive Genetic Algorithm (HAGA) is presented for solving it. In the HAGA, a local search approach is embedded into the Adaptive Genetic Algorithm (AGA) to improve its search performance. In addition, an unconventional crossover operator is given to meet the constraints of the DM problem. Simulation experiment results show that the HAGA is more effective to solve the DM problem than the AGA.