2008
DOI: 10.1007/978-0-387-09686-5_7
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Sums of Squares, Moment Matrices and Optimization Over Polynomials

Abstract: Abstract. We consider the problem of minimizing a polynomial over a semialgebraic set defined by polynomial equations and inequalities, which is NP-hard in general. Hierarchies of semidefinite relaxations have been proposed in the literature, involving positive semidefinite moment matrices and the dual theory of sums of squares of polynomials. We present these hierarchies of approximations and their main properties: asymptotic/finite convergence, optimality certificate, and extraction of global optimum solutio… Show more

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Cited by 643 publications
(732 citation statements)
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References 117 publications
(121 reference statements)
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“…It is well-known (and at the heart of current developments in optimization of polynomial functions, see [4,15] or the survey [5]) that SOS conditions with degree constraints of the form (3.3) can be phrased as semidefinite programs. Finding an (optimal) positive semidefinite matrix within an affine linear variety is known as semidefinite programming (see e.g.…”
Section: Approximations Based On the Real Nullstellensatzmentioning
confidence: 99%
See 1 more Smart Citation
“…It is well-known (and at the heart of current developments in optimization of polynomial functions, see [4,15] or the survey [5]) that SOS conditions with degree constraints of the form (3.3) can be phrased as semidefinite programs. Finding an (optimal) positive semidefinite matrix within an affine linear variety is known as semidefinite programming (see e.g.…”
Section: Approximations Based On the Real Nullstellensatzmentioning
confidence: 99%
“…Using a degree truncation approach, this allows to find sumof-squares-based polynomial identities which certify that a certain point is located outside of an amoeba or coamoeba. In particular, it is well known from recent lines of research in computational semialgebraic geometry (see, e.g., [4,5,15]) that these certificates can be computed via semidefinite programming (SDP).…”
Section: Introductionmentioning
confidence: 99%
“…This result will play a crucial role in our approach. We give a proof, based on [20], although some details are simplified.…”
Section: Positive Linear Forms and Real Radical Idealsmentioning
confidence: 99%
“…, p r be interpolation polynomials at the v i 's, i.e., such that p j (v i ) = δ i,j . An easy but crucial observation (made in [20]) is that we may assume that each p j has degree at most s − d. Indeed, we can replace each interpolation polynomial p j by its normal form modulo J with respect to a basis of R[x]/J. As such a basis can be obtained by picking a column basis of M s−d (Λ), its members are monomials of degree at most s − d, and the resulting normal forms of the p j 's are again interpolation polynomials at the v i 's but now with degree at most s−d.…”
Section: Theorem 11 [17] Letmentioning
confidence: 99%
“…The last decade has seen several developments in polynomial optimization [1,2,3]. In particular, a systematic procedure has been established to solve Polynomial Optimization Problems (POP) on compact basic semi-algebraic sets.…”
Section: Introductionmentioning
confidence: 99%