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

✍ Scribed by Jun Chen; Wenyu Sun; Raimundo J.B. de Sampaio

• Publisher: Elsevier Science
• Year: 2008
• Tongue: English
• Weight: 537 KB
• Volume: 56
• Category: Article
• ISSN: 0898-1221
• DOI: 10.1016/j.camwa.2008.05.010

✦ Synopsis

a b s t r a c t

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.