Weapon Target Assignment Based on Improved Artificial Fish Swarm Algorithm

Abstract

Weapon-Target Assignment (WTA) problem is the key of air defense command and control. Therefore, it is an urgent problem to complete the assignment quickly and efficiently. In this paper, an improved artificial fish swarm algorithm is proposed to improve assignment rate. Based on artificial fish swarm algorithm (AFSA), particle swarm optimization (PSO) is introduced to change the individual visual of artificial fish, and genetic operator is added to avoid the local extremum trap. The proposed algorithm is validated by the concrete cooperative air defense examples. The simulation results show that the algorithm improved the computational accuracy and the rate of convergence in solving weapon-target assignment problem in air defense.