Job shop scheduling with flexible routings based on analytical target cascading

For solving the large-scale job shop scheduling problems considering flexible routings with the characteristics of process planning and scheduling optimization, a hierarchical coordination optimization model based on analytical target cascading is proposed in this paper, which is divided into three sub-layers. The process planning layer is for optimal processing routes of all jobs, and multiple manufacturing units is formed by clustering all machines based on factor analysis method in the unit planning layer, and then the optimal scheduling solutions of jobs in each unit is obtained by adopting the improved genetic algorithm respectively in the job scheduling layer, which then gives feedback to the upper layer and repeatedly coordinates to obtain the global optimal solution. Finally, a typical computational experiment comparatively demonstrates the validity of the proposed model and algorithm, showing its efficient advantage in solving the large-scale job shop scheduling problems with flexible routings.