Robust solution of monotone stochastic linear complementarity problems

被引:15
|
作者
Xiaojun Chen
Chao Zhang
Masao Fukushima
机构
[1] Hirosaki University,Department of Mathematical Sciences, Faculty of Science and Technology
[2] Kyoto University,Department of Applied Mathematics and Physics, Graduate School of Informatics
来源
Mathematical Programming | 2009年 / 117卷
关键词
Stochastic linear complementarity problem; NCP function; Expected residual minimization; 90C15; 90C33;
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摘要
We consider the stochastic linear complementarity problem (SLCP) involving a random matrix whose expectation matrix is positive semi-definite. We show that the expected residual minimization (ERM) formulation of this problem has a nonempty and bounded solution set if the expected value (EV) formulation, which reduces to the LCP with the positive semi-definite expectation matrix, has a nonempty and bounded solution set. We give a new error bound for the monotone LCP and use it to show that solutions of the ERM formulation are robust in the sense that they may have a minimum sensitivity with respect to random parameter variations in SLCP. Numerical examples including a stochastic traffic equilibrium problem are given to illustrate the characteristics of the solutions.
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页码:51 / 80
页数:29
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