Research on rolling scheduling window

Key issues involved in rolling scheduling, including the determination of the number of work-pieces in the rolling scheduling window and the selection method of rolling scheduling windows, were studied. Based on resource constraints, a method for calculating the number of work-pieces in the rolling scheduling window was presented. To determine the entry of a specific work-piece into a rolling scheduling window, the powerful sorting capacity of neural network was employed and data mining was carried out among the actual scheduling schemes. In the process, the due time and priority of work pieces were considered. A computational test was given. Test results show that the proposed algorithm is effective in solving rolling scheduling problems.