Newton's method for quadratic stochastic programs with recourse

Xiaojun Chen, Liqun Qi, Robert S. Womersley

Research output: Journal article publicationJournal articleAcademic researchpeer-review

26 Citations (Scopus)

Abstract

Quadratic stochastic programs (QSP) with recourse can be formulated as nonlinear convex programming problems. By attaching a Lagrange multiplier vector to the nonlinear convex program, a QSP is written as a system of nonsmooth equations. A Newton-like method for solving the QSP is proposed and global convergence and local super-linear convergence of the method are established. The current method is more general than previous methods which were developed for box-diagonal and fully quadratic QSP. Numerical experiments are given to demonstrate the efficiency of the algorithm, and to compare the use of Monte-Carlo rules and lattice rules for multiple integration in the algorithm.
Original languageEnglish
Pages (from-to)29-46
Number of pages18
JournalJournal of Computational and Applied Mathematics
Volume60
Issue number1-2
DOIs
Publication statusPublished - 20 Jun 1995
Externally publishedYes

Keywords

  • Newton's method
  • Nonsmooth equations
  • Quadratic stochastic programs

ASJC Scopus subject areas

  • Applied Mathematics
  • Computational Mathematics

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