Feasible direction methods for stochastic programming problems

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42 Scopus citations


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
Issue number1
StatePublished - Dec 1980
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • General Mathematics


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


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