For artillery designers, the maximum muzzle velocity is desired, but also the muzzle pressure and ballistic efficiency, etc. To take the cannon as an example,when three objectives is considered at the same time, the design of the interior ballistic charge of the cannon can be truly multiplied objective optimization. In the selection of optimization methods, considering the disadvantages of traditional optimization algorithms, such as genetic algorithm and particle swarm algorithm, in terms of low convergence efficiency and solution accuracy, the bat algorithm with simple structure, fewer parameters and higher convergence efficiency is used to solve the problem of the interior ballistic performance optimization. The results show that the adopted multi-objective bat algorithm can effectively solve the multi-objective optimization problem of the interior ballistic performance of the cannon.The result is a series of Pareto optimal solutions, allowing designers to obtain a series of interior ballistic charging optimization schemes according to their needs, the optimization results also improve the interior ballistic performance and launch safety of the cannon.