An improved discrete Shuffled Frog Leaping Algorithm for cooperative Multi-Target assignment of BVR air combat

Multi-Target assignment is an important tactical factor of BVR (Beyond Visual Range) air combat. Based on the analysis of the basic Shuffled Frog Leaping Algorithm (SFLA), an Improved Discrete Shuffled Frog Leaping Algorithm is proposed to solve the problem of multi-target assignment in BVR air combat. The threat evaluation function and the multi-target assignment model of BVR air combat are established. The new SFLA adopts adaptive Strategy of Evolution Capability Control to update the subpopulations, which can avoid trapping into local extremum. In order to improve population diversity and speed up the convergence, the Strategy of Difference Disturbance is proposed. Simulation results indicate that the Improved Discrete SFLA is feasible and more effective when compared with other algorithm in finding out the multi-target assignment scenario.