Abstract:

At present, the types of munitions that can be carried by long-range multiple-launch rockets are becoming more and more diversified, which brings new challenges to the problem of optimization of munition aiming points. Aiming at the problems of previous algorithms' slow solution speed and poor solution quality in complex aiming point optimization models, this paper proposes an improved gray wolf algorithm, which enhances the algorithm's optimization ability and solution speed by incorporating a multi-layer multi-module coding strategy, adaptive mutation and simulated annealing strategy, and a single-decision-individual cross-guidance strategy. The experimental results show that, compared with the comparison algorithm, the algorithm proposed in this paper can maintain a faster solution speed when the combat forces of the red and blue sides change, and the comprehensive destructive effect of the selected aiming point is better, which has certain application value.

Key words: ammunition, point of aim, gray wolf algorithm, target destruction