Multi-object optimization of drilling trajectory is one of the keys to achieve efficient and safe drilling. The improvement of the optimization algorithms can get smaller trajectory length and less complexity in finding solutions to the trajectory optimization questions. However， the practicability of the trajectory optimization algorithm has not been verified. In this paper， the multi-object decomposition evolutionary algorithm combined with the adaptive penalty function， and the comprehensive evaluation method based on minimum fuzzy entropy are used to study the 3D sidetracking well trajectory optimization problem. The proposed methods were verified for their practicability with application in the drilling process intelligent control experimental system. They can provide reference and guidance for trajectory design in engineering practice， and provide reference for drilling trajectory tracking control.