Large-scale optimization of air-to-ground weapon effectiveness based on multi-level genetic algorithm

A novel multi-level genetic algorithm for large-scale programming of air-to-ground weapon firepower is proposed. By the new algorithm, the computing complexity problem of large-scale firepower programming is solved. The multi-level genetic algorithm is composed of two levels which are called upper-GA and bottom-GA. The bottom-GA is used for solving all the sub-models, and the results are sent to the upper-GA, while the upper-GA can dominate the bottom-GA through genetic operations. The simulation result shows that the multi-level genetic algorithm is effective and efficient. Moreover, the multi-level genetic algorithm can be applied to other complex system optimization problems.