### 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 language | English |
---|---|

Pages (from-to) | 1568-1572 |

Number of pages | 5 |

Journal | Proceedings of the American Control Conference |

Volume | 3 |

Publication status | Published - 1 Jan 1995 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Electrical and Electronic Engineering

### Cite this

*Proceedings of the American Control Conference*,

*3*, 1568-1572.

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

Research output: Contribution to journal › Conference article

*Proceedings of the American Control Conference*, vol. 3, pp. 1568-1572.

}

TY - JOUR

T1 - Theoretical foundation of a textured decomposition algorithm

AU - Huang, Garng Morton

AU - Hsieh, Shih Chieh

PY - 1995/1/1

Y1 - 1995/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0029190534&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029190534&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0029190534

VL - 3

SP - 1568

EP - 1572

JO - Proceedings of the American Control Conference

JF - Proceedings of the American Control Conference

SN - 0743-1619

ER -