Feasible direction methods for stochastic programming problems

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

A unified approach to stochastic feasible direction methods is developed. An abstract point-to-set map description of the algorithm is used and a general convergence theorem is proved. The theory is used to develop stochastic analogs of classical feasible direction algorithms.

Original languageEnglish (US)
Pages (from-to)220-229
Number of pages10
JournalMathematical Programming
Volume19
Issue number1
DOIs
StatePublished - Dec 1 1980
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Mathematics(all)

Keywords

  • Convergence
  • Feasible Direction Methods
  • Point-to-Set Maps
  • Stochastic Programming

Cite this