An improved black-winged kite algorithm for solving non-lethal kinetic strike parameters for moving targets.

With the advent of the intelligent era, enhancing the fire control performance of firearms has become a critical issue in military fields both domestically and internationally. As one of the key pieces of equipment for military and police forces worldwide to handle internal mass conflict incidents, non-lethal kinetic weapons rely on reasonable shooting parameters, which are a crucial prerequisite for ensuring non-lethal strikes against targets. To align with practical scenarios, this study constructed a non-lethal ballistic solution model for moving targets, converting it into a multi-constraint optimization problem. It computed the ideal terminal effectiveness applicable to Chinese subjects and proposed an enhanced BKA (IBKA). Based on the BKA, the IBKA integrates four improved strategies: Hammersley sequence initialization to improve population diversity, artificial lemming avoidance strategy to strengthen global search capability, Lévy flight step size to balance exploration and exploitation, and triangular mutation mechanism to prevent premature convergence. The IBKA was benchmarked against seven other popular optimization algorithms using the CEC2017 test suite. Comprehensive comparative analyses from multiple perspectives showed that the IBKA exhibits significant performance superiority. We further applied the IBKA and other algorithms to the shooting parameter solution problem under three different experimental cases. The results indicate that the IBKA has strong competitiveness in terms of both solution stability and result adaptability, and the solved shooting parameters can achieve fast, accurate, and effective strike effects.