In order to solve the problem of low computing speed in the process of state transition in the analytical modeling of UAV (unmanned aerial vehicle) swarm operation, a fourth-order Runge-Kutta method based on the row compressed storage was proposed. The UAV swarm operation process was divided into three stages according to the UAV swarm operation style, and continuous time Markov chain model was established for the state transition process of UAV swarm operation in stages. In the meantime, taking the reliability of UAV swarm to complete combat mission as the solving index, the fourth-order Runge-Kutta method was used to solve the Markov model, and the method based on row compressed storage was used to optimize the solving rate owing to the sparsity feature of the rate transfer matrix. Simulation results show that the established continuous time Markov chain model has better effectiveness and feasibility than other models. At the same time, compared with other algorithms, the proposed algorithm has higher computing speed and better reliability requirements to meet the accuracy of results, which further shows the superiority of it.