HGA-Based MES Dynamic Scheduling in a Complex Information Environment

Scheduling for manufacturing execution system (MES) is an important section of the overall running of the whole manufacturing system. Since MES is a bridge which links the upper planning system of the enterprise and the control system of the shop floor, various kinds of the information with different characteristics flow through the system. As a result, MES scheduling in this dynamic complex information environment becomes an important issue. Innovative and balanced perspectives of MES dynamic scheduling are discussed in this paper, and several achieved results and current developments are described. Firstly, the information environment of the MES and its effect on MES scheduling are analyzed. Then, the time decomposition-based MES dynamic scheduling strategy taking the balance of scheduling and execution into consideration is proposed. Moreover, a hybrid genetic algorithm-based dynamic scheduling framework is presented and several modified hybrid genetic algorithms (HGA) are developed. Satisfactory results are drawn from experiments and short comparative analysis about them is given at the end of the paper.