Just like the assembly line, the disassembly line has a variety of layouts. Selecting a reasonable disassembly line layout according to the disassembly environment is beneficial to improve the disassembly efficiency and reduce the space of the workshop. In order to improve the disassembly efficiency and balance rate, a U-shaped disassembly model is established to maximize disassembly profit and minimize disassembly energy consumption. The model focuses on the harmful risks of dismantling components. Robotic disassembly is the choice for those with higher risks, while manual disassembly is the choice for those with lower risks. In order to solve the balance problem of a U-shaped disassembly line, a multi-objective discrete Bat algorithm is proposed, which can provide a feasible solution for decision- makers. In order to verify the characteristics of the algorithm, we performed comparison with the current popular migratory bird optimization algorithm, artificial bee colony algorithm, non-dominated sorting genetic algorithm, and the decomposition-based multi-objective evolutionary algorithm. The experimental results show that the proposed algorithm is a good chioce to solve this problem. It has a strong search ability.