An immune particle swarm algorithm based on adaptive search strategy is proposed in this paper. Based on the traditional immune particle swarm algorithm, the sub populations are grouped on the fusion algorithm in parallel form, the size of each group is adjusted dynamically, and the search range is also adjusted, according to the maximum concentration of particles. Firstly, combing with the adjustment mechanism of concentration and the maximum value of concentration, the algorithm adjusts the number of sub populations, in order to make full use of the particle source. At the same time, the inferior sub-populations are vaccinated, and the maximum concentration of the particles is used to control the search range of the vaccine. Avoiding the degradation of population, the convergence accuracy and the global search ability of the algorithm are improved. A vehicle scheduling model of open-pit mine is established and simulation experiments are carried out. The simulation results show the proposed algorithm makes full use of the tramcar source, and has certain advantage and good engineering application value.