Global and Local Convergence of a New Affine Scaling Trust Region Algorithm for Linearly Constrained Optimization

作     者：Chao GU De Tong ZHU 

作者机构：School of Mathematics and InformationShanghai LiXin University of Commerce Department of MathematicsShanghai Normal University 

出 版 物：《Acta Mathematica Sinica,English Series》 (数学学报（英文版）)

年 卷 期：2016年第32卷第10期

页      面：1203-1213页

核心收录：

学科分类：12[管理学] 02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：Supported by National Natural Science Foundation of China(Grant Nos.11201304 and 11371253) the Innovation Program of Shanghai Municipal Education Commission 

主　　题：Linearly constrained optimization affine scaling trust region dwindling filter~ conver-gence 

摘      要：Chen and Zhang [Sci. China, Set. A, 45, 1390-1397 （2002）] introduced an affine scaling trust region algorithm for linearly constrained optimization and analyzed its global convergence. In this paper, we derive a new affine scaling trust region algorithm with dwindling filter for linearly constrained optimization. Different from Chen and Zhang＇s work, the trial points generated by the new algorithm axe accepted if they improve the objective function or improve the first order necessary optimality conditions. Under mild conditions, we discuss both the global and local convergence of the new algorithm. Preliminary numerical results are reported.