AN INEXACT LAGRANGE-NEWTON METHOD FOR STOCHASTIC QUADRATIC PROGRAMS WITH RECOURSE  

作　　者：ZhouChangyin HeGuoping 

机构地区：[1]Dept.ofMath.,ShanghaiJiaotongUniv.,Shanghai200240,China [2]CollegeofInformationScienceandEngineering,ShandongUniversityofScienceandTechnology,Taian271019,China

出　　处：《Applied Mathematics(A Journal of Chinese Universities)》2004年第2期229-238,共10页高校应用数学学报（英文版）（B辑）

基　　金：Partly supported by the National Natural Science Foundation of China( 1 0 1 71 0 5 5 )

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.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.

关 键 词：Lagrange-Newton method stochastic quadratic programming Monte Carlo simulation. 

分 类 号：O224[理学—运筹学与控制论]