Abstract
This paper considers a class of stochastic linear complementarity problems (SLCPs) with finitely many realizations. We first formulate this class of SLCPs as a minimization problem. Then, a partial projected Newton method, which yields a stationary point of the minimization problem, is presented. The global and quadratic convergence of the proposed method is proved under certain assumptions. Preliminary experiments show that the algorithm is efficient and the formulation may yield a solution with various desirable properties.
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This project was supported by the National Natural Science Foundation of China (Grant No. 61072144).
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Liu, H., Huang, Y. & Li, X. Partial projected Newton method for a class of stochastic linear complementarity problems. Numer Algor 58, 593–618 (2011). https://doi.org/10.1007/s11075-011-9472-7
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DOI: https://doi.org/10.1007/s11075-011-9472-7