Multi-missile aiming point optimization based on improved genetic algorithm

Aiming point optimization refers to the selection of the aiming point of a missile so that the strike effect on the target is at or near the best. As an example, a modified genetic algorithm is used to study the aiming point optimization problem of a multi-bullet missile striking the same target with different damage effects. Combined with the target vulnerability of the substation, suitable damage indicators and corresponding types of missile weapons are selected to establish the optimal aiming point solution model. In order to solve the defects of traditional genetic algorithm, an experience pool is established to store the dominant individuals to avoid the loss of dominant individuals and to retain the individuals with different genotypes to enhance the population diversity and avoid premature convergence of the algorithm. After calculations, the algorithm can effectively solve the problem of multi-bullet hybrid aiming point optimization, and the overall optimization result is better than the traditional a