A Dual-Population Genetic Algorithm for MTC Product Mixed-Model Assembly Line Balancing Problem with the Differences of Multi-skilled Workers and Process Difficulty

In order to solve the Z Company MTC series Mixed-model assembly line problems such as the unbalance of the workers, the low balance rate of the production line, the differences of multi-skilled workers and process difficulty when distributing the work, the mathematical model of assembly line balancing considering the difference of multi-skilled workers and process difficulty is established, which aims at the maximum balancing rate, the minimum load fluctuation of workstation and the minimum learning cost, the mathematical model is solved by double population genetic algorithm. Finally, the balance rate of mixed-model assembly line is increased from 73.2% to 93.3%, the production rhythm is reduced from 56.3 s to 44.2 s, the time-smoothness index of workstation is reduced from 8.96 to 1.74, and the learning cost is 800, the load difference of the workstation workers is reduced, which provides reference for the balance cost of the enterprise. The mathematical model of assembly line balancing considering the differences of multi-skilled workers and process difficulty is an effective method for the study of assembly line balancing ratio in workshop of Z company.