A New Nonmonotone Trust Region Algorithm for Solving Unconstrained Optimization Problems

A New Nonmonotone Trust Region Algorithm for Solving Unconstrained Optimization Problems

Year:    2014

Journal of Computational Mathematics, Vol. 32 (2014), Iss. 4 : pp. 476–490

Abstract

Based on the nonmonotone line search technique proposed by Gu and Mo (Appl. Math. Comput. 55, (2008) pp. 2158-2172), a new nonmonotone trust region algorithm is proposed for solving unconstrained optimization problems in this paper. The new algorithm is developed by resetting the ratio $ρ_k$ for evaluating the trial step $d_k$ whenever acceptable. The global and superlinear convergence of the algorithm are proved under suitable conditions. Numerical results show that the new algorithm is effective for solving unconstrained optimization problems.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.1401-m3975

Journal of Computational Mathematics, Vol. 32 (2014), Iss. 4 : pp. 476–490

Published online:    2014-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    15

Keywords:    Unconstrained optimization problems nonmonotone trust region method global convergence superlinear convergence.

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