A Retrospective Filter Trust Region Algorithm for Unconstrained Optimization
Yue Lu, Zhongwen Chen
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Abstract

In this paper, we propose a retrospective filter trust region algorithm for unconstrained optimization, which is based on the framework of the retrospective trust region method and associated with the technique of the multi-dimensional filter. The new algorithm gives a good estimation of trust region radius, relaxes the condition of accepting a trial step for the usual trust region methods. Under reasonable assumptions, we analyze the global convergence of the new method and report the preliminary results of numerical tests. We compare the results with those of the basic trust region algorithm, the filter trust region algorithm and the retrospective trust region algorithm, which shows the effectiveness of the new algorithm.

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Y. Lu and Z. Chen, "A Retrospective Filter Trust Region Algorithm for Unconstrained Optimization," Applied Mathematics, Vol. 1 No. 3, 2010, pp. 179-188. doi: 10.4236/am.2010.13022.

Conflicts of Interest

The authors declare no conflicts of interest.

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