Numerical research on the sensitivity of nonmonotone trust region algorithms to their parameters

Authors:
Jun Chen;Wenyu Sun;Raimundo J. B. de Sampaio
Affiliations:
School of Mathematics and Computer Science, Nanjing Normal University, Nanjing 210097, China and Department of Mathematics, Nanjing Xiaozhuang College, Nanjing 210017, China;School of Mathematics and Computer Science, Nanjing Normal University, Nanjing 210097, China;Pontifical Catholic University of Parana (PUCPR), Graduate Program in Production and Systems Engineering (PPGEPS), Rua Imaculada Conceicao, 1155, Prado Velho, CEP 81611-970 Curitiba, Parana, Brazi ...
Venue:
Computers & Mathematics with Applications
Year:
2008

Citing 6
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Abstract

In this paper, a numerical research on the sensitivity of nonmonotone trust region algorithms to their parameters is presented. We compare the numerical efficiency of two classes of nonmonotone trust region (NTR) algorithms in the context of unconstrained optimization. We examine the sensitivity of the algorithms to the parameters related to the nonmonotone technique and the initial trust region radius. We show that the numerical efficiency of nonmonotone trust region algorithms can be improved by choosing appropriate parameters. Based on extensive numerical tests, some efficient ranges of these parameters for nonmonotone trust region algorithms are recommended.