We consider the short-term scheduling of multistage continuous multiproduct plants. In the literature this problem is generally modeled as a monolithic mixed-integer program. In this paper we follow a closed-loop approach which starts from a decomposition of the problem into an operations planning and an operations scheduling problem. The operations planning problem consists in optimizing the operating conditions of the operations and can be formulated as a nonlinear program of moderate size. The solution to the operations planning problem provides a set of operations with fixed operating conditions, which have to be scheduled on the processing units of the plant. For solving this operations scheduling problem we use a novel mixed-integer linear programming formulation. Having computed a feasible production schedule, we return to the operations planning phase, where we re-optimize the operating conditions in such a way that we can guarantee the existence of a feasible s olution to the operations scheduling problem. We proceed with scheduling the operations again and iterate the planning and scheduling phases until a fixed-point solution has been reached. The new method is able to find good feasible schedules for complex benchmark instances within a few minutes of computation time on a standard PC
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.