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

被引：0
|
作者：
Zhou, Changyin [1 ]
Su, Rui [1 ]
Jiang, Zhihui [1 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2017年 / 2017卷
关键词：
QUADRATIC PROBLEMS; ALGORITHM;
D O I：
10.1155/2017/1564642
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
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页数：15
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