Abstract: In view of beyond-visual-range cooperative air combat, the model of Weapon-Target Assignment（WTA） is established, and a mixed Shuffled Frog Leaping Algorithm（SFLA） is proposed to solve the weapon-target assignment problem. Based on an unconstrained encoding, the algorithm combining the cross and mutation of genetic algorithm improves the convergence rate and the seeking ability for the global optimal result so that the local minimum is avoided. The simulation results show that the proposed algorithm is an effective algorithm to solve weapon-target assignment for cooperative air combat.

Key words: cooperative air combat, weapon-target assignment, shuffled frog leaping algorithm, genetic operator

摘要： 针对超视距多机协同空战中的火力分配（WTA）问题，建立了协同空战火力分配的数学模型，提出了采用混合蛙跳算法（SFLA）来求解协同空战火力分配问题，根据无约束化的编码方式，结合交叉、变异的遗传操作，提高了算法的收敛速度以及全局搜索能力，能有效避免陷入局部最优。仿真结果表明，所提出的混合蛙跳算法在解决协同空战火力分配问题中具有高效可行性。

关键词: 协同空战, 力分配, 混合蛙跳算法, 遗传算子