The Hierarchy of Local Minimums in Polynomial Optimization

Abstract

This paper studies the hierarchy of local minimums of a polynomial in the space. For this purpose, we first compute H-minimums, for which the first and second order optimality conditions are satisfied. To compute each H-minimum, we construct a sequence of semidefinite relaxations, based on optimality conditions. We prove that each constructed sequence has finite convergence, under some generic conditions. A procedure for computing all local minimums is given. When there are equality constraints, we have similar results for computing the hierarchy of critical values and the hierarchy of local minimums. Several extensions are discussed.

23 pages

References in corpus (3)

• Truncated K-moment problems in several variables
• Semidefinite Characterization and Computation of Real Radical Ideals
• Pure states, positive matrix polynomials and sums of hermitian squares

Cited by in corpus (1)

• All Real Eigenvalues of Symmetric Tensors