关键词: 信赖域算法, 非单调技术, 无约束优化, 锥模型, 全局收敛

Abstract: This paper presents a nonmonotonic trust region algorithm for unconstrained optimization problems based on a cone model, this algorithm takes advantage of the current iteration point order gradient information in solving the trust region subproblem. A new trust region radius selection mechanism is proposed, and it is compared with the classical trust region methods. At the same time, this paper sets some conditions, the global convergence under the conditions of these assumptions is proved. Experimental results show that the algorithm is effective in solving unconstrained optimization problems based on a cone model, and it expands the trust region algorithm applications.

Key words: trust region algorithms, nonmonotonic strategies, unconstrained optimization, cone model, global convergence