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.