A Study on optimization of Flow Line Production Based on the Genetic algorithm

The issue of vaccine flow line production was studied according to the actual flow line production requirements. In view of this issue, we took the minimum total production time as the objective, and built a 0-1 non-linear planning model under the premise of ensuring production reliability; optimized the same with the genetic algorithm. By selecting appropriate population initialization and adaptability function, we enabled it was not limited to local optimality and achieved the reduction in the number of iterations. The results show that the improved genetic algorithm can save about 2.3% of production time. On this basis, the total production time was further reduced to calculate the completion probability of the flow line tasks. Besides, the relationship between the reduced time proportion and the completion probability was simulated.