Bound-Constrained Polynomial Optimization Using Only Elementary Calculations
成果类型:
Article
署名作者:
de Klerk, Etienne; Lasserre, Jean B.; Laurent, Monique; Sun, Zhao
署名单位:
Tilburg University; Delft University of Technology; Centre National de la Recherche Scientifique (CNRS); Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Centrum Wiskunde & Informatica (CWI)
刊物名称:
MATHEMATICS OF OPERATIONS RESEARCH
ISSN/ISSBN:
0364-765X
DOI:
10.1287/moor.2016.0829
发表日期:
2017
页码:
834-853
关键词:
global optimization
semidefinite
minimization
relaxations
simplex
moments
摘要:
We provide a monotone nonincreasing sequence of upper bounds f(k)(H) (k >= 1) converging to the global minimum of a polynomial f on simple sets like the unit hypercube in R-n. The novelty with respect to the converging sequence of upper bounds in Lasserre [Lasserre JB (2010) A new look at nonnegativity on closed sets and polynomial optimization, SIAM J. Optim. 21: 864-885] is that only elementary computations are required. For optimization over the hypercube [0,1](n), we show that the new bounds f(k)(H) have a rate of convergence in O(1/root k). Moreover, we show a stronger convergence rate in O(1/k) for quadratic polynomials and more generally for polynomials having a rational minimizer in the hypercube. In comparison, evaluation of all rational grid points with denominator k produces bounds with a rate of convergence in O(1/k(2)), but at the cost of O(k(n)) function evaluations, while the new bound f(k)(H) needs only O(n(k)) elementary calculations.
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