Large-scale flow shop scheduling based on genetic algorithm

The flow shop scheduling problem has the property of modeling complexity, computational complexity, dynamic multi-constraint and multi-targeted. In recent years, a variety of evolutionary computation methods and the application of genetic algorithms have been gradually introduced into the production scheduling problem. In the paper, we design a new production scheduler program by using Matlab system and the method based on the genetic algorithm. Moreover, we use the actual production data to simulate the new scheduler. From the relevant simulation results we have verified that the differences existed in the optimal solution which from the combination of different crossover operators and mutation operator, and further obtained the better combination of crossover operator and mutation operator. Simulation results of our experiment show the feasibility and effectiveness of genetic algorithm for solving large-scale flow-shop scheduling.