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A polyhedral branch-and-cut approach to global optimization

A variety of nonlinear, including semidefinite, relaxations have been developed in recent years for nonconvex optimization problems. Their potential can be realized only if they can be solved with sufficient speed and reliability. Unfortunately, state-of-the-art nonlinear programming codes are signi...

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Published in:Mathematical programming 2005-06, Vol.103 (2), p.225-249
Main Authors: TAWARMALANI, Mohit, SAHINIDIS, Nikolaos V
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creator TAWARMALANI, Mohit
SAHINIDIS, Nikolaos V
description A variety of nonlinear, including semidefinite, relaxations have been developed in recent years for nonconvex optimization problems. Their potential can be realized only if they can be solved with sufficient speed and reliability. Unfortunately, state-of-the-art nonlinear programming codes are significantly slower and numerically unstable compared to linear programming software. In this paper, we facilitate the reliable use of nonlinear convex relaxations in global optimization via a polyhedral branch-and-cut approach. Our algorithm exploits convexity, either identified automatically or supplied through a suitable modeling language construct, in order to generate polyhedral cutting planes and relaxations for multivariate nonconvex problems. We prove that, if the convexity of a univariate or multivariate function is apparent by decomposing it into convex subexpressions, our relaxation constructor automatically exploits this convexity in a manner that is much superior to developing polyhedral outer approximators for the original function. The convexity of functional expressions that are composed to form nonconvex expressions is also automatically exploited. Root-node relaxations are computed for 87 problems from globallib and minlplib, and detailed computational results are presented for globally solving 26 of these problems with BARON 7.2, which implements the proposed techniques. The use of cutting planes for these problems reduces root-node relaxation gaps by up to 100% and expedites the solution process, often by several orders of magnitude.
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subjects Algorithms
Applied sciences
Approximation
Convex analysis
Digital Object Identifier
Exact sciences and technology
Linear programming
Mathematical programming
Nonlinear programming
Operational research and scientific management
Operational research. Management science
Optimization
Optimization algorithms
Polyhedra
Reliability theory. Replacement problems
Studies
title A polyhedral branch-and-cut approach to global optimization
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