In air defense firepower assignment, the traditional fire distribution model does not fully consider the firing efficiency factors of the fire channel, and under the condition of relatively sufficient fire resources, firepower resources are easy to waste and damage time could be delayed. By combining the fire advantage, flying time and threat degree, an new integrated air defense firepower assignment model is constructed. On this basis, a preprocessing multi group parallel cuckoo search algorithm (PMPCSA) is proposed for the optimal matching problem between the coming target, fire node and guidance nodes. The method uses Prolog intelligent planning language to build a target-fire node-guidance node matching rule library. In the rule library, the depth-first search is used to quickly generate a feasible matching pre-processing scheme of target-fire node-guidance nodes. Then, the multi group parallel cuckoo search algorithm is used to search the feasible allocation space. By introducing the idea of multi-population parallel optimization search and different populations given different control parameters, both the global exploration and the local development ability of the algorithm are taken into account, and the efficiency of algorithm optimization is effectively improved. Finally, the simulation results show the superiority of the integrated air defense firepower assignment model. At the same time, the results show that the proposed PMPCSA can effectively balance the global exploration and local development, which improves the global exploration ability while ensuring higher convergence speed.