file.pdf (1.54 MB)
Download file

Using redundancy to strengthen the relaxation for the global optimization of MINLP problems

Download (1.54 MB)
journal contribution
posted on 01.07.2010, 00:00 by Juan P. Ruiz, Ignacio E. Grossmann

In this paper we present a strategy to improve the relaxation for the global optimization of non-convex MINLPs. The main idea consists in recognizing that each constraint or set of constraints has a meaning that comes from the physical interpretation of the problem. When these constraints are relaxed part of this meaning is lost. Adding redundant constraints that recover that physical meaning strengthens the relaxation. We propose a methodology to find such redundant constraints based on engineering knowledge and physical insight.


Publisher Statement

This is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version is available at



Usage metrics