In order to achieve an optimal attack effect during the air combat in coordination, missile-target optimal assignment is an effective method in the process of attack in coordination. On the theoretical basis of operational efficiency and operational research, a missile-target optimal assignment mathematical model for multi-target attack in coordination is established. Then, based on the analysis of the basic particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm is proposed, and there are three improvements: 1. Adaptive adjustment of inertia weight; 2. Amelioration of particle velocity and position; 3. Betterment of optimization strategy. And this algorithm is applied in solving the missile-target optimal assignment problem of coordination air combat (MTACAC). The simulation result indicates that those advantageous improvements can expedite the convergence speed of the PSO algorithm and improve its local and global search ability. The IPSO algorithm, compared with the basic PSO algorithm and the genetic algorithm (GA), is better in finding the optimum assignment solution more quickly and effectively for the multi-target attack in coordination.