Share:


An Improved Adaptive Trust-Region Method for Unconstrained Optimization

    Hamid Esmaeili Affiliation
    ; Morteza Kimiaei Affiliation

Abstract

In this study, we propose a trust-region-based procedure to solve unconstrained optimization problems that take advantage of the nonmonotone technique to introduce an efficient adaptive radius strategy. In our approach, the adaptive technique leads to decreasing the total number of iterations, while utilizing the structure of nonmonotone formula helps us to handle large-scale problems. The new algorithm preserves the global convergence and has quadratic convergence under suitable conditions. Preliminary numerical experiments on standard test problems indicate the efficiency and robustness of the proposed approach for solving unconstrained optimization problems.

Keyword : unconstrained optimization, trust-region framework, nonmonotone technique, adaptive radius, convergence theory

How to Cite
Esmaeili, H., & Kimiaei, M. (2014). An Improved Adaptive Trust-Region Method for Unconstrained Optimization. Mathematical Modelling and Analysis, 19(4), 469-490. https://doi.org/10.3846/13926292.2014.956237
Published in Issue
Sep 1, 2014
Abstract Views
583
PDF Downloads
446
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.