| 带补偿的随机二次规划的近似Lagrange-Newton方法 |
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| 引用本文： | ZhouChangyin HeGuoping. 带补偿的随机二次规划的近似Lagrange-Newton方法[J]. 高校应用数学学报(英文版), 2004, 19(2): 229-238. DOI: 10.1007/s11766-004-0058-1 |
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| 作者姓名： | ZhouChangyin HeGuoping |
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| 作者单位： | [1]Dept.ofMath.,ShanghaiJiaotongUniv.,Shanghai200240,China [2]CollegeofInformationScienceandEngineering,ShandongUniversityofScienceandTechnology,Taian271019,China |
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| 基金项目： | Partly supported by the National Natural Science Foundation of China( 1 0 1 71 0 5 5 ) |
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| 摘 要： | In this paper, two-stage stochastic quadratic programming problems with equality constraints are considered. By Monte Carlo simulation-based approximations of the objective function and its first (second)derivative,an inexact Lagrange-Newton type method is proposed.It is showed that this method is globally convergent with probability one. In particular, the convergence is local superlinear under an integral approximation error bound condition.Moreover, this method can be easily extended to solve stochastic quadratic programming problems with inequality constraints.
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| 关 键 词： | 拉格朗日-牛顿中值定理 随机 规划 近似值 目标函数 最优化 误差理论 |
| 收稿时间： | 2003-04-24 |
An inexact lagrange-newton method for stochastic quadratic programs with recourse |
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| Zhou Changyin,He Guoping. An inexact lagrange-newton method for stochastic quadratic programs with recourse[J]. Applied Mathematics A Journal of Chinese Universities, 2004, 19(2): 229-238. DOI: 10.1007/s11766-004-0058-1 |
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| Authors: | Zhou Changyin He Guoping |
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| Affiliation: | Dept.of Math.,Shanghai Jiaotong Univ.,Shanghai 200240,China.;College of Information Science and Engineering,Shandong University of Science and Technology,Taian |
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| Abstract: | In this paper,two-stage stochastic quadratic programming problems with equality constraints are considered.By Monte Carlo simulation-based approximations of the objective function and its first(second)derivative,an inexact Lagrange-Newton type method is proposed.It is showed that this method is globally convergent with probability one.In particular,the convergence is local superlinear under an integral approximation error bound condition.Moreover,this method can be easily extended to solve stochastic quadratic programming problems with inequality constraints. |
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| Keywords: | Lagrange-Newton method stochastic quadratic programming Monte Carlo simulation. |
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