A smooth penalty-based sample average approximation method for stochastic complementarity problems
Sample average approximation method is one of the effective methods in the stochastic optimization. A smooth penalty-based sample average approximation method for stochastic nonlinear complementarity problems is presented in this paper. Based on a smooth penalty function, a reformulation is proposed...
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| Published in | Journal of computational and applied mathematics Vol. 287; pp. 20 - 31 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
15.10.2015
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| ISSN | 0377-0427 1879-1778 |
| DOI | 10.1016/j.cam.2015.03.017 |
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| Abstract | Sample average approximation method is one of the effective methods in the stochastic optimization. A smooth penalty-based sample average approximation method for stochastic nonlinear complementarity problems is presented in this paper. Based on a smooth penalty function, a reformulation is proposed for the equivalent problem of EV formulation for stochastic complementary problems and it is proven that its solutions are existent under some mild assumptions. An implementable sample average approximation method for the reformulation is further established and its convergence is analyzed. The numerical results for some test examples are reported at last to show efficiency of the proposed method. |
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| AbstractList | Sample average approximation method is one of the effective methods in the stochastic optimization. A smooth penalty-based sample average approximation method for stochastic nonlinear complementarity problems is presented in this paper. Based on a smooth penalty function, a reformulation is proposed for the equivalent problem of EV formulation for stochastic complementary problems and it is proven that its solutions are existent under some mild assumptions. An implementable sample average approximation method for the reformulation is further established and its convergence is analyzed. The numerical results for some test examples are reported at last to show efficiency of the proposed method. |
| Author | Tong, Hengqing Wei, Min He, Suxiang |
| Author_xml | – sequence: 1 givenname: Suxiang surname: He fullname: He, Suxiang email: hesux@whut.edu.cn – sequence: 2 givenname: Min surname: Wei fullname: Wei, Min – sequence: 3 givenname: Hengqing surname: Tong fullname: Tong, Hengqing |
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| Cites_doi | 10.1007/s10957-008-9358-6 10.1090/S0025-5718-09-02206-6 10.1007/s11424-011-0948-2 10.1080/10556780600627610 10.1287/moor.1070.0260 10.1080/02331930801954177 10.1007/s10479-006-6169-8 10.1137/040608544 10.1137/070702187 10.1137/070704277 10.1080/02331930701617320 10.1007/s10957-009-9606-4 10.1007/s101070050024 10.1142/S0217595910002569 10.1137/050638242 10.1023/A:1021814225969 10.1007/BF01582255 10.1287/moor.1050.0160 |
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| Keywords | Penalty function 90C30 Stationary point 90C15 Stochastic complementarity problems Sample average approximation method Convergence |
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| SubjectTerms | Approximation Computational efficiency Convergence Equivalence Mathematical analysis Mathematical models Optimization Penalty function Sample average approximation method Stationary point Stochastic complementarity problems Stochasticity |
| Title | A smooth penalty-based sample average approximation method for stochastic complementarity problems |
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