A trust region method for conic model to solve unconstrained optimization

被引：48
|
作者：
Di, S [1 ]
Sun, WY [1 ]
机构：
[1] NANJING UNIV, DEPT MATH, NANJING 210008, PEOPLES R CHINA
来源：
OPTIMIZATION METHODS & SOFTWARE | 1996年 / 6卷 / 04期
基金：
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词：
unconstrained optimization; conic model; trust region; nonquadratic model; nonlinear programming;
D O I：
10.1080/10556789608805637
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A trust region method for conic models to solve unconstrained optimization problems is proposed. We analyze the trust region approach for conic models and present necessary and sufficient conditions for the solution of the associated trust region subproblems. A corresponding numerical algorithm is developed and has been tested for 19 standard test functions in unconstrained optimization. The numerical results show that this method is superior to some advanced methods in the current software libraries. Finally, we prove that the proposed method has global convergence and Q-superlinear convergence properties.
引用
收藏
页码：237 / 263
页数：27
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