A hybrid trust region algorithm for unconstrained optimization

Authors:
Yigui Ou
Affiliations:
Department of Mathematics, Hainan University, Haikou 570228, China
Venue:
Applied Numerical Mathematics
Year:
2011

Citing 7
Cited 0

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Abstract

This paper presents a hybrid trust region algorithm for unconstrained optimization problems. It can be regarded as a combination of ODE-based methods, line search and trust region techniques. A feature of the proposed method is that at each iteration, a system of linear equations is solved only once to obtain a trial step. Further, when the trial step is not accepted, the method performs an inexact line search along it instead of resolving a new linear system. Under reasonable assumptions, the algorithm is proven to be globally and superlinearly convergent. Numerical results are also reported that show the efficiency of this proposed method.