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 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.

中文翻译：

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一种求解无约束优化的基于圆锥模型的交替方向信任域新方法

本文采用一种新的基于圆锥模型的交替方向信任域方法求解无约束优化问题。利用交替方向法，在两个正交方向上分两步求解新的圆锥模型信任域子问题。这一新思想克服了圆锥模型子问题难以求解的缺点。然后建立该方法在某些合理条件下的全局收敛性。数值实验表明，该方法在解决子问题上可能优于狗腿法，尤其是对于大规模问题。