A new adaptive trust region approach for solving the unconstrained optimization problems

Abstract

We introduce a new algorithm for unconstrained optimization problems within a trust-region framework. The method features an adaptive nonmonotone strategy to enhance the performance. Also, an effective adaptive strategy is employed to update the trust region radius. We establish the algorithm's global convergence under the standard assumptions and confirm its efficiency through numerical experiments.