In this paper, an improved multi-­objective black­hole(MOBH) evolutionary algorithm is applied to optimization of a tubular linear permanent magnet synchronous motor(LPMSM). The MOBH evolutionary algorithm has good performance in convergence rate, population diversity, population convergence and subspecies acquisition in different Pareto regions. Based on the motor model and introduction of the MOBH algorithm, a multi-­objective optimization model regarding to thrust, ratio between thrust and volume and copper loss(efficiency) is established. The Pareto dominated solution space corresponding to the three objectives provides a more comprehensive and intuitive optimal solution space. The final optimal solution can be comprehensively selected according to the application requirements and the actual physical value distribution range. The relationship between the distribution of Pareto dominant solutions and the main design variables under a single objective condition is discussed. Finally, the accuracy of the calculation of the main design indexes is verified by the prototype experiment.