Abstract: To solve the problem of assembly line balance problem with a determined production cycle and improve the balance degree of assembly line, a single-objective assembly line balance optimization model was established. According to the different priority weighting rate of optimization goals, the linear weight sum method was used to establish the model. The optimization goals of the model are the assembly line smoothing index and assembly line balance rate, considering the assembly job allocation, the number of workstations and other factors. The hybrid algorithm of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm for solving the model was improved. The new fitness function and distance information matrix were constructed. Finally, numerical experiments are carried out on the classical examples. The experimental results show that the improved model and algorithm can improve the balance of the assembly line to a greater extent and verify the effectiveness of the model and algorithm.

Key words: assembly line balancing problem, genetic algorithm, ant colony optimization algorithm, simple objective optimization