title: Advances in mixed-integer programming methods for chemical production scheduling.
abstract: The goal of this paper is to critically review advances in the area of chemical production scheduling over the past three decades and then present two recently proposed solution methods that have led to dramatic computational enhancements. First, we present a general framework and problem classification and discuss modeling and solution methods with an emphasis on mixed-integer programming (MIP) techniques. Second, we present two solution methods: (a) a constraint propagation algorithm that allows us to compute parameters that are then used to tighten MIP scheduling models and (b) a reformulation that introduces new variables, thus leading to effective branching. We also present computational results and an example illustrating how these methods are implemented, as well as the resulting enhancements. We close with a discussion of open research challenges and future research directions.
authors.affiliation: Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Wisconsin 53706; email: maravelias@wisc.edu.
authors.forename: Sara
authors.initials: S
authors.lastname: Velez
authors.forename: Christos T
authors.initials: CT
authors.lastname: Maravelias
mesh_terms: D000465:Algorithms; D002617:Chemical Industry / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012984:Software; D013997:Time Factors
keywords: chemical supply chain; process operations; process systems engineering; reformulations; solution methods; valid inequalities