AN AFFINE SCALING DERIVATIVE-FREE TRUST REGION METHOD WITH INTERIOR BACKTRACKING TECHNIQUE FOR BOUNDED-CONSTRAINED NONLINEAR PROGRAMMING  

作　　者：GAO Jing ZHU Detong 

机构地区：[1]Department of Mathematics,Shanghai Normal University

出　　处：《Journal of Systems Science & Complexity》2014年第3期537-564,共28页系统科学与复杂性学报（英文版）

基　　金：supported by the National Science Foundation of China under Grant No.11371253

摘　　要：This paper proposes an arlene scaling derivative-free trust region method with interior backtracking technique for bounded-constrained nonlinear programming. This method is designed to get a stationary point for such a problem with polynomial interpolation models instead of the objective function in trust region subproblem. Combined with both trust region strategy and line search technique, at each iteration, the affine scaling derivative-free trust region subproblem generates a backtracking direction in order to obtain a new accepted interior feasible step. Global convergence and fast local convergence properties are established under some reasonable conditions. Some numerical results are also given to show the effectiveness of the proposed algorithm.

关 键 词：Affine scaling backtracking technique box constrains derivative-free optimization non-linear programming trust region method. 

分 类 号：O221.2[理学—运筹学与控制论]