A hybrid trust region algorithm for unconstrained optimization
The author considers unconstrained optimization problem consisting in minimization of a continuously differentiable function \(f: \mathbb{R}^n\to\mathbb{R}\). The paper presents a hybrid trust region algorithm for solving the problem. Global and superlinear convergence of the proposed algorithm is proved. The efficiency of the algorithm is demonstrated on numerical tests presented in the concluding part of the paper.
scientific article; zbMATH DE number 5895499
scientific article