An ant colony algorithm for master production scheduling optimization

The product demand forecast play an important role in drawing out an efficient and reasonable master production schedule for various manufacturing enterprise. In this paper, the demand forecasting model based on BP neural network is proposed to address the master production scheduling optimization problem. Moreover, a simulation example and several error indexes have been design to evaluate and analyze the performance of the proposed method. Otherwise, in order to satisfy the demand of production balance and the products due date, this paper also proposes a bi-objectives mathematical model for solving the master production scheduling optimization problem. The performance measures investigated are maximum the equipment utilization and minimum the tardiness penalty of the production inventory. The experimental results illustrate that the proposed method is a very effective algorithm.