A multi-constrained human-robot collaborative disassembly line balancing problem was proposed for U-shaped disassembly lines in order to address the issues that existing studies on human-robot collaborative disassembly lines neither simultaneously consider differences in human and robotic task time and task attribute constraint, nor incorporate robot procurement costs into the long-term costs of collaboration. An integer programming model for the U-shaped disassembly line was constructed, with the objectives of minimizing the number of workstations, the idle time balancing index, and the long-term cost. Constraints considering various problem characteristics, including human-robot task attributes, human-robot task time, and AND/OR precedence relations were incorporated. An improved hybrid clonal simulated annealing algorithm was proposed. Double-layer encoding and decoding were designed, along with mutation and crossover operations specifically considering the problem characteristics. Cloning operations were introduced to enhance the local search capability of the algorithm, and a two-stage annealing process was implemented to accelerate convergence speed. Gurobi software was applied to solve small and medium-scale problems, and the results were compared with those obtained by the algorithm to verify the correctness and effectiveness of the model and algorithm. The cost variations of different disassembly line modes with the estimated operational time of the disassembly line were calculated and compared. Results demonstrate that the proposed model possesses the advantage of agile disassembly line planning.