Research on Multi-Objective Assembly Line Balancing Optimization Based on Grey Relational Analysis

This paper presents a multi-objective assembly line balancing optimization method based on grey relational analysis and simulated annealing algorithm. For the multiple optimization objectives in assembly line balancing, grey relational analysis is first used to integrate the relative importance of different objectives into a single objective function, thereby reducing the complexity of multi-objective optimization. Then, the simulated annealing algorithm is employed to globally search while considering the weight relationships between objectives, gradually approaching the optimal solution. Simulation results verify that different weight combinations significantly impact the distribution of workload and production cycle time across workstations. The results show that the proposed method effectively balances multiple objectives, achieves an equitable workload distribution, and optimizes the production cycle time. Particularly, in reducing workload differences between workstations and shortening production cycle time, the proposed model demonstrates strong global optimization capabilities, offering a feasible solution for the practical application of assembly line.