Decomposition modeling and solution methods for large-scale flexible job-shop scheduling problems

For the large-scale flexible job-shop scheduling problem, a scheduling method based on workpiece similarity is adopted to reduce the problem scale, a mathematical model for decomposed scheduling is established, and an improved whale optimization algorithm is designed to solve it. Firstly, the workpieces are classified according to the raw material, process steps, final product type, and the number of the same processes. After classification, the workpieces in the same category are batch-scheduled according to their delivery deadlines. During the optimization process, a three-segment coding method is designed, and based on this coding method, a calculation method for the distance between whale individuals is proposed, enabling whale individuals to identify and swim towards the better and nearest guiding individual within their search range. In the iterative optimization process, the IPOX crossover method and the MPX crossover method are introduced, and the movement rules of whale individuals are improved, allowing whale individuals to approach the global optimal solution more quickly and accurately.