A new trust region method with adaptive radius for unconstrained optimization

Abstract

In this paper, we propose a new adaptive trust region method for unconstrained optimization problems. In the new method, we use the previous and the current iterative information and a new update rule to define the trust region radius at each iterate. The global and superlinear convergence properties of the method are established under reasonable assumptions. Preliminary numerical results show that the new method is efficient and attractive for unconstrained optimization problems.