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27 April 2024
 
  » arxiv » math.OC/0103170

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Minimizing Polynomial Functions
Pablo A. Parrilo ; Bernd Sturmfels ;
Date 26 Mar 2001
Journal Algorithmic and quantitative real algebraic geometry, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol. 60, pp. 83--99, AMS, 2003. ISBN: 0-8218-2863-0.
Subject Optimization and Control; Algebraic Geometry; Commutative Algebra MSC-class: 13J30, 90C22, 13P10, 65H10 | math.OC math.AC math.AG
AbstractWe compare algorithms for global optimization of polynomial functions in many variables. It is demonstrated that existing algebraic methods (Gröbner bases, resultants, homotopy methods) are dramatically outperformed by a relaxation technique, due to N.Z. Shor and the first author, which involves sums of squares and semidefinite programming. This opens up the possibility of using semidefinite programming relaxations arising from the Positivstellensatz for a wide range of computational problems in real algebraic geometry. This paper was presented at the Workshop on Algorithmic and Quantitative Aspects of Real Algebraic Geometry in Mathematics and Computer Science, held at DIMACS, Rutgers University, March 12-16, 2001.
Source arXiv, math.OC/0103170
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