An interior-point trust-region algorithm for general symmetric cone programming

Ye Lu; Ya-Xiang Yuan

doi:10.1137/040611756

An interior-point trust-region algorithm for general symmetric cone programming

Ye Lu, Ya-Xiang Yuan

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

17 Citations (Scopus)

Abstract

An interior-point trust-region algorithm is proposed for minimizing a general (nonconvex) quadratic objective function in the intersection of a symmetric cone and an affine subspace. The algorithm uses a trust-region model to ensure descent on a suitable merit function. Global first-order and second-order convergence results are proved. Numerical results are presented. © 2007 Society for Industrial and Applied Mathematics.

Original language	English
Pages (from-to)	65-86
Journal	SIAM Journal on Optimization
Volume	18
Issue number	1
DOIs	https://doi.org/10.1137/040611756
Publication status	Published - 2007
Externally published	Yes

Research Keywords

Interior-point algorithm
Symmetric cone
Trust-region subproblem

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title = "An interior-point trust-region algorithm for general symmetric cone programming",

abstract = "An interior-point trust-region algorithm is proposed for minimizing a general (nonconvex) quadratic objective function in the intersection of a symmetric cone and an affine subspace. The algorithm uses a trust-region model to ensure descent on a suitable merit function. Global first-order and second-order convergence results are proved. Numerical results are presented. {\textcopyright} 2007 Society for Industrial and Applied Mathematics.",

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author = "Ye Lu and Ya-Xiang Yuan",

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T1 - An interior-point trust-region algorithm for general symmetric cone programming

AU - Lu, Ye

AU - Yuan, Ya-Xiang

PY - 2007

Y1 - 2007

N2 - An interior-point trust-region algorithm is proposed for minimizing a general (nonconvex) quadratic objective function in the intersection of a symmetric cone and an affine subspace. The algorithm uses a trust-region model to ensure descent on a suitable merit function. Global first-order and second-order convergence results are proved. Numerical results are presented. © 2007 Society for Industrial and Applied Mathematics.

AB - An interior-point trust-region algorithm is proposed for minimizing a general (nonconvex) quadratic objective function in the intersection of a symmetric cone and an affine subspace. The algorithm uses a trust-region model to ensure descent on a suitable merit function. Global first-order and second-order convergence results are proved. Numerical results are presented. © 2007 Society for Industrial and Applied Mathematics.

KW - Interior-point algorithm

KW - Symmetric cone

KW - Trust-region subproblem

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-39449113661&origin=recordpage

U2 - 10.1137/040611756

DO - 10.1137/040611756

M3 - RGC 21 - Publication in refereed journal

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SP - 65

EP - 86

JO - SIAM Journal on Optimization

JF - SIAM Journal on Optimization

IS - 1

ER -

An interior-point trust-region algorithm for general symmetric cone programming

Abstract

Research Keywords

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