Abstract: In response to the problems of inefficient design process, incomplete optimization schemes, and non-intuitive optimization results in the traditional structural optimization design of the Stewart platform, based on deep analysis of the kinematic characteristics of the Stewart platform, the kinematic equations of the platform are established, and the reachable workspace and flexible workspace of the platform are obtained through simulation technology. The multi-objective ant lion (MOALO) algorithm is applied to the structural optimization design of the Stewart platform, and with the Jacobian matrix condition number and available operability as optimization objectives, multiple sets of optimization solutions, namely Pareto optimization solution sets, are obtained through simulation software. Taking the Stewart platform used as a motion simulator as an example for specific optimization design analysis, the effectiveness and feasibility of the algorithm are verified by solving the volume ratio of flexible workspace. In the structural optimization design of the Stewart platform, the MOALO algorithm has better convergence and coverage in multi-objective optimization problems compared to evolutionary genetic algorithm, multi-objective particle swarm optimization algorithm, etc. , and it is more in line with practical multi-objective optimization engineering design.