4.6 Article

Polynomial programming: LP-relaxations also converge

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SIAM JOURNAL ON OPTIMIZATION
卷 15, 期 2, 页码 383-393

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SIAM PUBLICATIONS
DOI: 10.1137/040603942

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real algebraic geometry; global optimization; semidefinite programming relaxations; linear programming relaxations

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We consider the global minimization of a multivariate polynomial on a compact semialgebraic set. Using a result of Krivine [J. Analyse Math., 12 (1964), pp. 307-326; C. R. Acad. Sci. Paris, 258 (1964), pp. 3417-3418], it is shown that LP-relaxations based on products of the original constraints, in the spirit of the reformulation-linearization technique procedure of Sherali and Adams, converge to the global optimum. This extends to compact semialgebraic sets, previous results known for polytopes, and 0-1 programs. The asymptotic behavior of the LP-relaxations is also analyzed, and it is shown that in important cases, finite convergence cannot occur.

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