In order to realize the high maneuverability of the electromagnetic catapult and the high power density of the linear catapult motor of the land-based unmanned aerial vehicle, a multi-population genetic algorithm with elite retention (MPGAER) was proposed to optimize the maximum power density of motor. It takes flux density and current density as constraints, and optimizes the structure parameters of the motor with its strong search ability and fast convergence speed, and compares with the initial scheme based on magnetic circuit method and the optimization results of traditional genetic algorithm. The results show that, compared with the initial scheme design, MPGAER can reduce the motor mass by 6.25%, increase the power density by 10%, and improve the dynamic performance of the motor; the motor power density of the MPGAER optimized design is higher than the genetic algorithm design result, which indicates that the proposed method effectively solves the problems of easy convergence to the local best advantage and poor optimization effect in the optimization process.