Master production scheduling of a pet food plant using a rolling horizon optimization methodology - Cusimano, Joan (2023)
This work addresses the Master Production Scheduling problem (MPS) of a pet food manufacturing plant. The production process comprises several stages, starting with the dosing of raw materials and ending with the packaging and storage of the final product. The plant has a fixed number of production lines, being the critical equipment the extruders and packaging machines available. Given a medium-term horizon (3 to 5 months) disaggregated into weeks, for each line the production volumes per product, which are associated to different families, must be defined. A mixed-integer linear mathematical model (MILP), considering the main constraints of the problem, combined with a Rolling Horizon algorithm to solve the complete horizon has been developed. The proposed methodology has been applied to the MPS problem of a large-scale industrial facility that produces hundreds of products and families. Based on the problem’s dimensions, a parameter analysis of the algorithm has been performed to find the best balance between time and solution quality. As a result, by applying the proposed methodology considerable improvements were obtained regarding key indicators such as minimum batch size per family, compliance with the stock policy, and solution times compared with the current method.