Nonmonotone retrospective conic trust region method for unconstrained optimization

Lijuan Zhao; Wenyu Sun

doi:10.3934/naco.2013.3.309

Article Contents

2013, Volume 3, Issue 2: 309-325. Doi: 10.3934/naco.2013.3.309

This issue Previous Article A modification of the forward-backward splitting method for maximal monotone mappings Next Article An adaptive wavelet method and its analysis for parabolic equations

Nonmonotone retrospective conic trust region method for unconstrained optimization

Lijuan Zhao^1, and
Wenyu Sun^2,

1.
School of Mathematical Sciences, Jiangsu Key Laboratory for NSLSCS, Nanjing Normal University, Nanjing 210023
2.
School of Mathematical Sciences, Jiangsu Key Laboratory for NSLSCS, Nanjing Normal University, Nanjing 210046

Received: June 2012

Revised: January 2013

Published: April 2013

Abstract / Introduction Related Papers Cited by

Abstract

We propose a retrospective conic trust region method for unconstrained optimization. It can be regarded as an extension of the retrospective trust region method based on a quadratic model which was first proposed by Bastin et al (2010). Nonmonotone technique is added to accelerate the speed of the algorithm. Under some mild conditions, the sequence generated by our algorithm converges to a stationary point. Numerical tests on a set of standard testing problems confirm the efficiency of our new method.

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Mathematics Subject Classification: 65K05, 90C30.

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