Theoretical foundation of a textured decomposition algorithm

Garng Morton Huang, Shih Chieh Hsieh

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

A Textured Decomposition Method (TDM) is proposed for large-scale convex optimization problems, in which a problem is reduced to a set of more tractable subproblems by rotatingly fixing some complicating (interaction or coupling) variables. The approach is appealing since mutually independent subproblems can be solved in parallel. Accordingly, the TDM solves a large-scale convex optimization problem by iteratively solving a sequence of concurrent subproblems. Necessary and sufficient conditions to guarantee that the converged solution of the TDM be the optimal solution of the original problem are addressed.

Original languageEnglish
Pages (from-to)1568-1572
Number of pages5
JournalProceedings of the American Control Conference
Volume3
Publication statusPublished - 1 Jan 1995
Externally publishedYes

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Convex optimization
Decomposition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Theoretical foundation of a textured decomposition algorithm. / Huang, Garng Morton; Hsieh, Shih Chieh.

In: Proceedings of the American Control Conference, Vol. 3, 01.01.1995, p. 1568-1572.

Research output: Contribution to journalConference article

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