Dealing with the airspace conflict detection problem, this paper applies the GJK algorithm and genetic algorithm combined with a neural network to enhance the elite retention strategy to get the airspace conflict detection algorithm and conflict resolution method. Airspace conflicts can be solved under different airspace usage conditions and requirements. Meanwhile, for UAVs with strong time correlation, the scheme can meet the demand of maintaining a time series between airspace applications within the same airspace cluster to accomplish the combat mission cluster. Simulation results show that the algorithm can efficiently and accurately detect the conflicting airspace and number in the airspace conflict problem and give a scheme to realize the global optimal combat effect. At the same time, the fitting and comparison results show that the combined algorithm has higher efficiency and accuracy than the traditional single algorithm. The algorithm is highly efficient and accurate in actual airspace conflict resolution.