A New Trust Region Method with Self-adaptive Update Rules for Unconstrained Optimization

We propose a new class of trust region method with a self-adaptive trust region radius update rules. Trust region radius is automatically adjusted according to the weighted sum of the ratios between the actual reduction and the prediction reduction. At some assumptions, the global convergence are proved. Finally, numerical experiments show that the method is robust and effective.