Multi-intersected/recursive textured algorithms for large-scale convex optimization problems

Garng Morton Huang, Shih Chieh Hsieh

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

In this paper, we extend our Textured Algorithm [1]-[4] to multi-intersected textured models. We also describe the recursive textured decomposition process as a tree, in which we can obtain the overall solution by consolidating the end subsystem solutions. The proposed algorithms, their properties, and the theorems for exact convergence are then addressed. The worst-case time complexity of the algorithm with complete tree structure, in which parents in the same recursion level have the same number of children, is analyzed. Examples are given to demonstrate the use of the algorithms and the trade-off among the number of recursion levels, the number of sequential computing steps, and problem size reduction.

Original languageEnglish
Pages (from-to)1121-1126
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
Publication statusPublished - 1 Dec 1995
Externally publishedYes

Fingerprint

Large-scale Optimization
Convex optimization
Recursive Algorithm
Convex Optimization
Optimization Problem
Recursion
Tree Structure
Time Complexity
Subsystem
Trade-offs
Decomposition
Decompose
Computing
Theorem
Demonstrate

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

Cite this

Multi-intersected/recursive textured algorithms for large-scale convex optimization problems. / Huang, Garng Morton; Hsieh, Shih Chieh.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 2, 01.12.1995, p. 1121-1126.

Research output: Contribution to journalConference article

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