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A class of smoothing SAA methods for a stochastic linear complementarity problem

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  • Indexed by:Journal Article

  • Date of Publication:2012-01-01

  • Journal:Numerical Algebra, Control and Optimization

  • Included Journals:Scopus

  • Volume:2

  • Issue:1

  • Page Number:145-156

  • ISSN:21553289

  • Abstract:A class of smoothing sample average approximation (SAA) methods is proposed for solving a stochastic linear complementarity problem, where the underlying function is the expected value of stochastic function. Existence and convergence results to the proposed methods are provided and some numerical results are reported to show the efficiency of the methods proposed.

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