A new alternating direction trust region method based on conic model for solving unconstrained optimization
A new alternating direction trust region method based on conic model for solving unconstrained optimization
复制标题
一种基于二次曲线模型求解无约束优化的新交替方向信赖域方法
DOI：
10.1080/02331934.2020.1745793
复制
发表时间：
2020
期刊：
影响因子：
2.2
通讯作者：
Dang Chuangyin
中科院分区：
文献类型：
--
作者：
Zhu Honglan;Ni Qin;Jiang Jianlin;Dang Chuangyin
本文将一种新的基于锥模型的交替方向信赖域方法用于求解无约束优化问题。利用交替方向搜索法，在两个正交方向上分两步求解新锥模型信赖域子问题。该方法克服了锥模型子问题求解困难的缺点。在一定的条件下证明了该方法的全局收敛性。数值实验表明，该方法对子问题的求解，尤其是对大规模问题的求解，可能优于折线法。
In this paper, a new alternating direction trust region method based on conic model is used to solve unconstrained optimization problems. By use of the alternating direction search method, the new conic model trust region subproblem is solved by two steps in two orthogonal directions. This new idea overcomes the shortcomings of conic model subproblem which is difficult to solve. Then the global convergence of the method under some reasonable conditions is established. Numerical experiment shows that this method may be better than the dogleg method to solve the subproblem, especially for large-scale problems.