Articles

A NEW ADAPTIVE TRUST REGION ALGORITHM FOR OPTIMIZATION PROBLEMS

  • Zhou SHENG ,
  • Gonglin YUAN ,
  • Zengru CUI
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  • College of Mathematics and Information Science, Guangxi University, Nanning 530004, China

Received date: 2016-07-09

  Revised date: 2016-10-13

  Online published: 2018-04-25

Supported by

Supported by the National Natural Science Foundation of China (11661009), the Guangxi Science Fund for Distinguished Young Scholars (2015GXNSFGA139001), the Guangxi Natural Science Key Fund (2017GXNSFDA198046), and the Basic Ability Promotion Project of Guangxi Young and Middle-Aged Teachers (2017KY0019).

Abstract

It is well known that trust region methods are very effective for optimization problems. In this article, a new adaptive trust region method is presented for solving unconstrained optimization problems. The proposed method combines a modified secant equation with the BFGS updated formula and an adaptive trust region radius, where the new trust region radius makes use of not only the function information but also the gradient information. Under suitable conditions, global convergence is proved, and we demonstrate the local superlinear convergence of the proposed method. The numerical results indicate that the proposed method is very efficient.

Cite this article

Zhou SHENG , Gonglin YUAN , Zengru CUI . A NEW ADAPTIVE TRUST REGION ALGORITHM FOR OPTIMIZATION PROBLEMS[J]. Acta mathematica scientia, Series B, 2018 , 38(2) : 479 -496 . DOI: 10.1016/S0252-9602(18)30762-8

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