A Research of Multi-Constrained Two-sided Mixed-model Assembly Line Balancing Problem Based on Genetic Algorithm

For the multi-constrained two-sided mixed-model assembly line balancing problem is currently less studied, a multi-objective two-sided mixed-model assembly line balance mathematical model is constructed. The model takes the minimum number of paired stations, maximum assembly line balance rate and minimum smoothness index as the goal under the consideration of zoning constraints and cooperative operation constraints. The model is solved by improved genetic algorithms which adopts the coding method based on sequence combination, and improves the initialization population, decoding, etc. The efficiency of genetic algorithm is effectively improved. Finally, an interior assembly line of an automobile company is used as an example to analyze the effectiveness of the model and algorithm. Therefore, its application can effectively improve the production efficiency of the assembly line.