TC25 titanium alloy is a material widely used in the aviation manufacturing field. In order to balance the machining efficiency and surface quality in milling, an improved particle swarm optimization algorithm was proposed to optimize the machining parameters. Firstly, based on the machining efficiency model and surface quality model, the optimization model of TC25 titanium alloy milling was established. Then, the good point set method was introduced to initialize the population of the particle swarm optimization algorithm, and the adaptive parameters were constructed based  the symbiosis/competition mechanism. At the same time, the optimal updating strategies of individual and population in particle swarm optimization algorithms are established based on dominance relationship and calling mechanism. Finally, the workpiece is machined using optimized parameters and its surface roughness is measured. Through the measurement of 6 points, it is found that the surface roughness after optimization is reduced by 16.7% and the machining efficiency is increased by 36.2%. The roughness instrument verified the optimization results, which can provide a valuable reference for the subsequent processing of TC25 titanium alloy.