Abstract
In order to adapt to the changing battlefield situation and improve the combat effectiveness of air combat, the problem of air battle allocation based on Bayesian optimization algorithm (BOA) is studied. First, we discuss the number of fighters on both sides, and apply cluster analysis to divide our fighter into the same number of groups as the enemy. On this basis, we sort each of our fighters’ different advantages to the enemy fighters, and obtain a series of target allocation schemes for enemy attacks by first in first serviced criteria. Finally, the maximum advantage function is used as the target, and the BOA is used to optimize the model. The simulation results show that the established model has certain decision-making ability, and the BOA can converge to the global optimal solution at a faster speed, which can effectively solve the air combat task assignment problem.
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