Nash equilibrium strategies approach for aerial combat based on elite re-election particle swarm optimization

A multi-combat step dynamic target assignment optimization model is built based on Nash equilibrium concept by considering the joint survival probability and weapons consumption factors for dynamic multi-strategy UAV cooperative attack. In building the model the value function calculation for the two belligerent parties and the solving method of bimatrix game Nash equilibrium point are applied. Then, an elite re-election particle swarm optimization (ERPSO) is proposed based on the elite reelection mechanism; therefore, the diversity of individuals can be increased when leading capacity of group extreme value is deficient through cloning, mutation and re-initialization operation. The advantages of traditional particle swarm optimization (PSO) algorithm such as simple structure, fast convergence are retained, but the shortcoming of falling into local minimum is corrected. Finally, the ERPSO algorithm is applied to the dynamic target assignment model to solve the Nash equilibrium point for obtaining accurate hybrid strategies for both sides. It is confirmed that the real-time demands and accuracy are satisfied, and the validity of the proposed model and method is established.