Integration of Planning and Scheduling for Large-Scale Multijob Multitasking Batch Plants

In this study, we propose a novel framework to integrate planning and scheduling for a multijob multitasking large-scale industrial plant. The key contribution of this study is that the proposed approach can address problems involving multijob batch plants where there are no fixed products or recipes, i.e., the job specifications could vary with respect to client requirements. The proposed approach includes a long-term planning model and a short-term scheduling model that are integrated using an iterating framework, where the two models interact with each other and share information in every iteration. A long-term planning model is developed for a multijob batch plant that provides key planning decisions, including daily processing targets and the required number of workers to achieve those targets to the scheduling model. In addition, to allow the integration of such a planning model with scheduling, we propose an iterative integration scheme that includes a calibration scheme combined with a rolling horizon approach. The proposed scheme also considers variations in job arrivals and allows to account for the latest job arrivals in the planning model. The proposed framework was validated using an actual industrial case study from the analytical services sector, which is focused on carrying out analyses on samples that are ordered by clients. The results obtained show an average increase of 8.27% in terms of profit when the models are integrated using the rolling horizon approach in comparison to solving the models sequentially.