| Autor: |
Németh, Sándor Zoltán, Xiao, Lianghai |
| Rok vydání: |
2019 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
In this paper, we study the stochastic linear complementarity problems on extended second order cones (stochastic ESOCLCP). We first convert the problem to a stochastic mixed complementarity problem on the nonegative orthant (SMixCP). Enlightened by the idea of Chen and Lin(2011), we introduce the Conditional Value-at-risk (CVaR) method to measure the loss of complementarity in the stochastic case. A CVaR - based minimisation problem is introduced to achieve a solution which is "good enough" for the complementarity requirement of the original SMixCP. Smoothing function and sample average approximation methods are introduced and the the problem is converted to a form which can be solved by Levenberg-Marquardt smoothing SAA algorithm. At the end of the paper a numerical example illustrates our results. |
| Databáze: |
arXiv |
| Externí odkaz: |
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