Multi-man–robot collaborative disassembly line balancing optimization via mixed-integer programming and genetic Jaya algorithm

Investigating disassembly line balancing problems (DLBP) is essential for the cleaner production and sustainable reuse of large-scale end-of-life products. Multi-man-robot shared-station and man-robot interactive collaboration are two critical approaches to enhance the efficiency of disassembly lines. This study combines these two approaches to innovatively design a multi-man–robot collaborative disassembly station and develops the corresponding DLBP (MMRC-DLBP). To effectively address this problem, a mixed-integer programming (MIP) model is established to solve the global minima of the number of stations, the number of operators (workers and robots), the total disassembly time and the idle balancing index. Given the limitations of MIP models in solving the NP-hard problem, a genetic Jaya algorithm (GJA) combining the strengths of the genetic algorithm and the Jaya algorithm is proposed to optimize the large-scale MMRC-DLBP. Subsequently, correctness of the MIP model and GJA is mutually verified by solving a small-scale case. The superior performance of the GJA in solving DLBP is demonstrated by solving the medium-scale and large-scale cases and comparing the results with those of existing algorithms from the literature. Finally, GJA is applied to the balancing optimization of a multi-man-robot collaborative disassembly line for obsolete televisions, and its superiority in solving MMRC-DLBP is confirmed by comparing the results with those of the five published algorithms.