Production Scheduling Of Batch Processes Based On Adaptive De Algorithm

Production scheduling problems and traditional differential evolution(DE) are analyzed in this paper. Taking the minimum of total completion time as the objective function of production scheduling, a production scheduling model is established for batch processes in process industry. Considering that the performance of the traditional DE algorithm is sensitive to the parameter settings, an adaptive control evolution strategy is used to control the parameter scale factor F and crossover probability CR to solve the problem of parameter settings. Taking a practical production problem as a scheduling example, the established model and adaptive DE algorithm are applied to implement the production scheduling simulation. The simulation results show that compared with the ant colony system(ACS) algorithm, the adaptive DE algorithm is effective and feasible.