A new modified nonmonotone adaptive trust region method for unconstrained optimization

Authors:
Zhaocheng Cui;Boying Wu
Affiliations:
Department of Mathematics and Physics, Shandong Jiaotong University, Jinan, China 250023;Department of Mathematics, Harbin Institute of Technology, Harbin, P. R. China 150080
Venue:
Computational Optimization and Applications
Year:
2012

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Abstract

In this paper, we present an adaptive trust region method for solving unconstrained optimization problems which combines nonmonotone technique with a new update rule for the trust region radius. At each iteration, our method can adjust the trust region radius of related subproblem. We construct a new ratio to adjust the next trust region radius which is different from the ratio in the traditional trust region methods. The global and superlinear convergence results of the method are established under reasonable assumptions. Numerical results show that the new method is efficient for unconstrained optimization problems.