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SAMPLE AVERAGE APPROXIMATION METHOD FOR A CLASS OF STOCHASTIC VARIATIONAL INEQUALITY PROBLEMS 被引量:7

SAMPLE AVERAGE APPROXIMATION METHOD FOR A CLASS OF STOCHASTIC VARIATIONAL INEQUALITY PROBLEMS
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摘要 This paper considers a class of stochastic variational inequality problems. As proposed by Jiang and Xu (2008), by using the so-called regularized gap function, the authors formulate the problems as constrained optimization problems and then propose a sample average approximation method for solving the problems. Under some moderate conditions, the authors investigate the limiting behavior of the optimal values and the optimal solutions of the approximation problems. Finally, some numerical results are reported to show efficiency of the proposed method.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2011年第6期1143-1153,共11页 系统科学与复杂性学报(英文版)
基金 This research is partly supported by the National Natural Science Foundation of China under Grant Nos. 71171027 and 11071028, the Fundamental Research Funds for the Central Universities under Grant No. DUT11SX11, and the Key Project of the National Natural Science Foundation of China under Grant No. 71031002.
关键词 CONVERGENCE gap function sample average approximation method stochastic variational inequality. 变分不等式问题 随机 平均 样本 逼近法 约束优化问题 逼近问题 数值结果
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参考文献14

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同被引文献16

  • 1刘勇进,张立卫,王银河.线性二阶锥规划的一个光滑化方法及其收敛性(英文)[J].数学进展,2007,36(4):491-502. 被引量:6
  • 2Yan Qin BAI,Guo Qiang WANG.Primal-dual Interior-point Algorithms for Second-order Cone Optimization Based on a New Parametric Kernel Function[J].Acta Mathematica Sinica,English Series,2007,23(11):2027-2042. 被引量:9
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  • 6LIU Y C, ZHANG Y. Penalized sample average approximation methods for stochastic mathematical programs with complementarity constraints [ J ]. Mathematics of Operations Research, 2011,36 (4) : 670 - 694.
  • 7SHUANG C, PANG L P, GUO F F, et al. Stochastic methods based on Newton method to the stochastic variational inequality problem with constraint conditions [J]. Mathematical and Computer Modeling[J], 2012,55 (3) :779 - 784.
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