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Concluding Remarks

First, we review the different types of chemical production scheduling problems and the mixed-integer programming (MIP) models that have been proposed to address them. Second, we overview four solution methods for MIP scheduling models: (1) algorithms for the generation of unit-, task-, material-, and resource-specific nonuniform grids used to formulate multi-grid discrete-time models; (2) tightening inequalities based on constraint propagation algorithms; (3) reformulations and branching strategies; and (4) a discrete-continuous algorithm that harnesses the advantages of discrete and continuous-time models. To showcase the effectiveness of these methods, we present industrial case studies as well as results from extensive computational studies. We close with a discussion of the open challenges in the areas and some future research directions.