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Random Coordinate Minimization Method with Eventual Transverse Directions for Constrained Polynomial Optimization

Conference Paper
Publication Date:
2019
abstract:
In this paper, we propose a novel algorithm for the solution of polynomial optimization problems. In particular, we show that, under mild assumptions, such problems can be solved by performing a random coordinate-wise minimization and, eventually, when a coordinate-wise minimum has been reached, an univariate minimization along a randomly chosen direction. The theoretical results are corroborated by a numerical example where the given procedure is compared with several other methods able to solve polynomial problems.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
stochastic methods; optimization; polynomial programming problems; sum of squares
List of contributors:
Possieri, Corrado
Authors of the University:
POSSIERI CORRADO
Handle:
https://iris.cnr.it/handle/20.500.14243/411779
Published in:
PROCEEDINGS OF THE IEEE CONFERENCE ON DECISION & CONTROL
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http://www.scopus.com/record/display.url?eid=2-s2.0-85082450286&origin=inward
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