New Problem Representation for the Simultaneous Resolution of Batching and Scheduling in Multiproduct Batch Plants

Abstract

The large number of studies addressing the scheduling problem in multiproduct batch plants with different units operating in parallel and out of phase at each stage highlights its importance in achieveing their efficient operation, as well as the difficulty and the number of variants that may arise in solving this problem. Scheduling is usually solved in a simplified way, considering as data the number and size of the required batches to satisfy the demand. More recently, models have been developed that simultaneously solve the batching, that is, determine the number and size of batches, and scheduling problems, generally achieving better solutions. However, these models are of great computational complexity due to their combinatorial nature, and, therefore, the development of efficient models that allow addressing large problems remains a great challenge. This work presents a new approach, where production paths are defined that allows obtaining the solution in short computation times. Then, a novel discrete-time mixed-integer linear formulation (MILP) for the simultaneous resolution of batching and scheduling in a multistage batch plant is presented and its performance is considered in detail.