Relaxation methods for monotropic programs

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We propose a dual descent method for the problem of minimizing a convex, possibly nondifferentiable, separable cost subject to linear constraints. The method has properties reminiscent of the Gauss-Seidel method in numerical analysis and uses the ε-complementary slackness mechanism introduced in Bertsekas, Hosein and Tseng (1987) to ensure finite convergence to near optimality. As special cases we obtain the methods in Bertsekas, Hosein and Tseng (1987) for network flow programs and the methods in Tseng and Bertsekas (1987) for linear programs.

Original languageEnglish (US)
Pages (from-to)127-151
Number of pages25
JournalMathematical Programming
Volume46
Issue number1-3
DOIs
StatePublished - Jan 1990
Externally publishedYes

Keywords

  • Dual descent
  • Tucker tableau
  • elementary vector
  • monotropic program

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

Fingerprint

Dive into the research topics of 'Relaxation methods for monotropic programs'. Together they form a unique fingerprint.

Cite this