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Discretization-based methods have been proposed for solving nonconvexoptimization problems with bilinear terms such as the pooling problem. Thesemethods convert the original nonconvex optimization problems into mixed-integerlinear programs (MILPs). In this paper we study tightening methods for theseMILP models for the pooling problem, and derive valid constraints using upperbounds on bilinear terms. Computational results demonstrate the effectivenessof our methods in terms of reducing solution time.

Tightening Discretization-based MILP Models for the Pooling Problem using Upper Bounds on Bilinear Terms