High-Dimensional Cooperative Jamming Strategy Optimization via a Two-Stage Differential Evolution Algorithm

To counter the complex threat of multi-missile coordinated attacks in modern warfare, this paper constructs a high-dimensional nonlinear optimization model for a scenario involving five Unmanned Aerial Vehicles (UAVs) cooperatively jamming three incoming missiles. The model’s core challenges lie in its 40-dimensional decision space and a “black-box” objective function evaluated by a high-fidelity simulator. To effectively solve this, this paper innovatively represent the entire strategy of the UAV swarm as a matrix-form decision variable and design a two-stage Differential Evolution (DE) algorithm. The first stage rapidly generates a high-quality initial solution through model decoupling and parallel optimization. The second stage then performs a fine-tuned global coupled optimization based on this initial solution to fully account for the synergistic and redundant effects among jamming units. The results demonstrate that this method can effectively manage high-dimensional complexity, yielding a final cooperative strategy that achieves a total effective obscuration time (union) of 27.34 seconds against all missile threats, validating the robustness and superiority of the model and algorithm for solving large-scale tactical planning problems.