一种改进的BFGS信任域方法

2010 Third International Joint Conference on Computational Science and Optimization Pub Date : 2010-05-28 DOI:10.1109/CSO.2010.106

Yunlong Lu, Xiaowei Jiang, Yueting Yang

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引用次数: 4

摘要

我们提出了一种新的信任域方法，该方法采用了改进的BFGS更新和Amijio线搜索。该方法利用了函数和梯度的信息，保证了信赖域子问题的Hessian矩阵的正定。在一定的假设条件下，给出了该算法的全局收敛性和超线性收敛性。最后，通过数值实验验证了该方法的有效性。

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A Modified BFGS Trust Region Method

We propose a new trust region method that employs both the modified BFGS update and Amijio line search. The method exploits the information of function and gradient, and ensures the Hessian matrix of trust region subproblem positive-definite. At some assumptions, the global convergence and superlinear convergence property are proposed. Finally, numerical experiments show that the method is efficient.

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2010 Third International Joint Conference on Computational Science and Optimization

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