Collaborative Optimization Strategy for Multi-period Planning and Scheduling with Data-driven Yield Model

The planning and scheduling of production determine the economic benefits of enterprise greatly. In this paper, an integration strategy of multi-period collaborative optimization for production planning and scheduling based on data-driven yield model is proposed. Both expert knowledge and historical production data are used to build the yield model of unit. Considering the purchase plan of raw material, inventory of current raw material, sales price of product and equipment production, the multi-period planning and scheduling collaborative optimization strategy (MPSCOS) is established dynamically. The plan and industry production scheme of raw material processing can quickly be obtained by MPSCOS, which helps gain maximum benefit under the condition of safe production. The application effect of MPSCOS is introduced by a practical case. It shows that the model based on dynamic production process can effectively improve the maintainability; the yield model based on data-driven is more accurate than the traditional yield model, as well as the model updating is convenient; the collaborative model of planning and scheduling can effectively connect the planning with scheduling, and further improve the business efficiency of enterprises.