Jamming resource optimization is an important link in current EW mission planning. Aimed at he problems that multi-objective optimization algorithm is easy to fall into local optimization and there is too much trouble in converges in three-objective optimization, a multi-aircraft jamming resource optimization method is proposed based on improved multi-objective moth-to-flame algorithm. Firstly, based on the multi-objective moth-to-flame algorithm, Tent chaotic map is utilized for initializing the population, increasing the diversity and uniformity of the solution and improving the search ability of the algorithm. And then, the induction of decision factor and Lévy flight is to make the algorithm accept not only the current solution with a certain probability, but also jump out of the current solution according to the disturbance and search again, enhancing the search ability of the algorithm. Finally, the widely distributed reference points are used to solve the convergence problem of the multi-objective moth-to-flame algorithm in the three-objective function. The simulation results show that this algorithm is better in convergence and population diversity than the MOEA/D algorithm and the NSMFO algorithm, and the convergence result of this method is stable, achieving the purpose of assisting combat decision