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.

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

Possieri Corrado
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.
2019
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
Inglese
58th IEEE Conference on Decision and Control
2019-December
541
546
9781728113982
http://www.scopus.com/record/display.url?eid=2-s2.0-85082450286&origin=inward
11-13/12/2019
Nice, France
stochastic methods
optimization
polynomial programming problems
sum of squares
1
none
Calafiore, Giuseppe C.; Novara, Carlo; Possieri, Corrado
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/411779
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