Distributed Iterative Aggregation Algorithms for Box-Constrained Minimization Problems and Optimal Routing in Data Networks

Wei K. Tsai, Garng Morton Huang, John K. Antonio

Research output: Contribution to journalArticle

17 Citations (Scopus)


A new gradient projection algorithm using iterative aggregation and disaggregation is proposed and analyzed for box-constrained minimization problems. In a distributed computation model, the algorithm is shown to converge. As an important application, we also show how the algorithm is applied to optimal routing in a large interconnected data communication network. The aggregation/disaggregation method proposed results in a multilevel hierarchical clustering of a large network, which naturally fits the hierarchical topological structure of large networks. An implementation of the algorithm for a 52-node network shows that the serial version of the algorithm has a savings of 35 percent of the computational time as compared to a path-formulated gradient projection code developed by Bertsekas, Gendron, and Tsai, which is among the fastest existing programs for path-formulated optimal routing.

Original languageEnglish
Pages (from-to)34-46
Number of pages13
JournalIEEE Transactions on Automatic Control
Issue number1
Publication statusPublished - 1 Jan 1989
Externally publishedYes


ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this