Abstract: This study aims to improve the accuracy of source location in case of inaccurate first arrival time. It investigates the influence of disturbances to the theoretical first arrival on source location, and then discuses the deviation of source location due to the divergence of particle swarm optimization (PSO) algorithm. The PSO algorithm characterized by high-speed global search is combined with differential evolution algorithm. After differential mutation of any two individuals in the population, new individuals are generated by hybridization and greedy selection operation. This process increases the population diversity, reduces the divergence of source location, and improves the accuracy of source location. Ultimately, a source location method based on the PSO and differential evolution algorithms is established for microseismic monitoring. Test data from the theoretical model show that the proposed method has higher accuracy in case of a disturbed first arrival time, whereas the divergence of source location is reduced compared with traditional PSO method. The applied effect of the established method is further verified by inversion of the actual microseismic data.