A Quasi-Monte-Carlo-Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse

Zhou Changyin; Su Rui; Jiang Zhihui

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A Quasi-Monte-Carlo-Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse

机译：基于随机蒙特程序的拟蒙特卡罗线性方程组可行序列系统

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A two-stage stochastic quadratic programming problem with inequality constraints is considered. By quasi-Monte-Carlo-based approximations of the objective function and its first derivative, a feasible sequential system of linear equations method is proposed. A new technique to update the active constraint set is suggested. We show that the sequence generated by the proposed algorithm converges globally to a Karush-Kuhn-Tucker (KKT) point of the problem. In particular, the convergence rate is locally superlinear under some additional conditions.

机译：考虑具有不等式约束的两阶段随机二次规划问题。通过基于目标函数及其一阶导数的近似蒙特卡洛近似，提出了一种可行的线性方程组序贯方法。建议了一种更新主动约束集的新技术。我们表明，所提出的算法生成的序列全局收敛到问题的Karush-Kuhn-Tucker（KKT）点。特别地，在某些附加条件下，收敛速度局部为超线性。

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《Mathematical Problems in Engineering》 |2017年第8期|1564642.1-1564642.15|共15页
作者
Zhou Changyin; Su Rui; Jiang Zhihui;
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Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China;

Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China;

Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China;

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A Quasi-Monte-Carlo-Based Feasible Sequential System of Linear Equations Method for Stochastic Programs with Recourse

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