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
We consider the problem of planning and scheduling physical and chemical processes on a multiproduct chemical batch production plant. Such a plant consists of several multi-purpose processing units and storage facilities of limited capacity. Given primary requirements for final products, the problem consists in generating an appropriate set of batches for each process and scheduling the processing of those batches on the processing units subject to different types of technological constraints. In the literature the short-term planning problem is generally modeled as a monolithic mixed-integer linear program. Due to the combinatorial nature of the problem, those models generally cannot be used when dealing with problem instances of practical size. In this paper we propose a two-level approach which is based on a decomposition of the problem into a batching and a batch scheduling problem. We formulate the batching problem as a mixed-integer linear program, which allows for considering the execution of processes on alternative processing units with unit-specific lower and upper bounds on the batch sizes. The batch scheduling problem can be solved using a specific method known from the literature. We report on computational results for a sample production process from the chemical engineering literature.
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