An adaptive genetic algorithm based on the greedy algorithm that improves mutation operation is proposed for the case of Multi-UAV searching for targets in specific areas.The search area is rasterized according to the prior intelligence,and the collaborative search model based on the state updating cycle is established considering UAV performance constraints.The 0-1 encoding is introduced to associate the UAV heading control sequence with the search probability.Considering that the repeated detection of a certain area by airborne radar could improve the search probability to a certain extent,the greedy mutation strategy adding the greedy operator is proposed,and the strategy selection threshold is introduced to realize the dynamic adjustment of the mutation strategy according to the variation of the search probability,so as to improve the local search ability of the algorithm in the later stage of the process.The simulation results show that the improved adaptive genetic algorithm performs better and has strong search ability and robustness.