Logic cuts for processing networks with fixed charges

John N. Hooker, Hong Yan, Ignacio E. Grossmann, Ramesh Raman

Abstract: We show how some simple logical constraints can substantially accelerate the solution of mixed integer linear programming (MILP) models for the design of chemical processing networks. These constraints are easily generated in a preprocessing stage and can be applied symbolically. They represent a new class of cuts, “logic cuts”, that cut off 0–1 solutions without changing the optimal objective function value. We establish their elementary properties and identify all possible logic cuts for the processing network problems. Preliminary computational results are presented, using OSL.