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Title: A smoothing SAA method for a stochastic mathematical program with complementarity constraints (English)
Author: Zhang, Jie
Author: Zhang, Li-wei
Author: Wu, Yue
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 57
Issue: 5
Year: 2012
Pages: 477-502
Summary lang: English
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Category: math
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Summary: A smoothing sample average approximation (SAA) method based on the log-exponential function is proposed for solving a stochastic mathematical program with complementarity constraints (SMPCC) considered by Birbil et al. (S. I. Birbil, G. Gürkan, O. Listes: Solving stochastic mathematical programs with complementarity constraints using simulation, Math. Oper. Res. 31 (2006), 739–760). It is demonstrated that, under suitable conditions, the optimal solution of the smoothed SAA problem converges almost surely to that of the true problem as the sample size tends to infinity. Moreover, under a strong second-order sufficient condition for SMPCC, the almost sure convergence of Karash-Kuhn-Tucker points of the smoothed SAA problem is established by Robinson's stability theory. Some preliminary numerical results are reported to show the efficiency of our method. (English)
Keyword: smoothing SAA method
Keyword: log-exponential function
Keyword: stochastic mathematical program with complementarity constraints
Keyword: almost sure convergence
Keyword: complementarity constraints
Keyword: sample average approximation
Keyword: stability analysis
MSC: 90C15
MSC: 90C33
idZBL: Zbl 1265.90223
idMR: MR2984615
DOI: 10.1007/s10492-012-0028-5
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Date available: 2012-08-19T22:02:15Z
Last updated: 2020-07-02
Stable URL: http://hdl.handle.net/10338.dmlcz/142912
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