On the Solution of Large-Scale Chemical Production Scheduling Problems

In this talk, we first present an overview of the different types of chemical production scheduling problems and the mixed-integer programming (MIP) models that have been proposed to address them. We then discuss four solution methods we have recently developed to enhance the solution of 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) four classes of tightening inequalities based on a demand propagation algorithms; (3) a branch-and-bound algorithm designed to harness parallel computational resources; and (4) a number of reformulations and branching strategies. We also present computational results showing that the proposed methods lead to computational improvements of two to four orders of magnitude, thereby enabling us to address problems that were thought to be intractable.