A nonmonotone trust region method based on simple quadratic models

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摘要

In this paper, a new nonmonotone trust region algorithm with simple quadratic models is proposed. Unlike traditional nonmonotone trust region method, our trust region subproblem is very simple by using a new scale approximation of the minimizing function’s Hessian. The global convergence of the proposed algorithm is established under some reasonable conditions. Numerical tests on a set of large scale standard test problems are presented and show that the new algorithm is efficient and robust.

论文关键词:65K05,90C30,Large scale unconstrained optimization,Simple quadratic model,Nonmonotone trust region method,Global convergence

论文评审过程:Received 13 January 2012, Revised 7 January 2014, Available online 12 May 2014.

论文官网地址:https://doi.org/10.1016/j.cam.2014.04.026