Open AccessA modified filter nonmonotone adaptive retrospective trust region method
Author(s) -
Xiangling Ding,
Quan Qu,
Xinyi Wang
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0253016
Subject(s) - line search , robustness (evolution) , trust region , convergence (economics) , mathematical optimization , computer science , filter (signal processing) , mathematics , chemistry , biochemistry , computer security , economics , radius , computer vision , gene , economic growth
In this paper, aiming at the unconstrained optimization problem, a new nonmonotone adaptive retrospective trust region line search method is presented, which takes advantages of multidimensional filter technique to increase the acceptance probability of the trial step. The new nonmonotone trust region ratio is presented, which based on the convex combination of nonmonotone trust region ratio and retrospective ratio. The global convergence and the superlinear convergence of the algorithm are shown in the right circumstances. Comparative numerical experiments show the better effective and robustness.