Stochastic R0 matrix linear complementarity problems

Haitao Fang, Xiaojun Chen, Masao Fukushima

Research output: Journal article publicationJournal articleAcademic researchpeer-review

81 Citations (Scopus)


We consider the expected residual minimization formulation of the stochastic R0 matrix linear complementarity problem. We show that the involved matrix being a stochastic R0 matrix is a necessary and sufficient condition for the solution set of the expected residual minimization problem to be nonempty and bounded. Moreover, local and global error bounds are given for the stochastic R0 matrix linear complementarity problem. A stochastic approximation method with acceleration by averaging is applied to solve the expected residual minimization problem. Numerical examples and applications of traffic equilibrium and system control are given.
Original languageEnglish
Pages (from-to)482-506
Number of pages25
JournalSIAM Journal on Optimization
Issue number2
Publication statusPublished - 1 Dec 2007
Externally publishedYes


  • Expected residual minimization
  • R matrix 0
  • Stochastic linear complementarity problem

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software


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