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A modified filter nonmonotone adaptive retrospective trust region method

Author

Listed:
  • Xianfeng Ding
  • Quan Qu
  • Xinyi Wang

Abstract

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.

Suggested Citation

  • Xianfeng Ding & Quan Qu & Xinyi Wang, 2021. "A modified filter nonmonotone adaptive retrospective trust region method," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
    • Handle: RePEc:plo:pone00:0253016
    DOI: 10.1371/journal.pone.0253016
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    References listed on IDEAS

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    1. Zhaocheng Cui & Boying Wu, 2012. "A new modified nonmonotone adaptive trust region method for unconstrained optimization," Computational Optimization and Applications, Springer, vol. 53(3), pages 795-806, December.
    2. Ju-liang Zhang & Yong Wang, 2003. "A new trust region method for nonlinear equations," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 58(2), pages 283-298, November.
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