An Approximate Quasi‐Newton Bundle‐Type Method for Nonsmooth Optimization

Jie Shen, Li-Ping Pang and Dan Li

Abstract and Applied Analysis, 2013, vol. 2013, issue 1

Abstract: An implementable algorithm for solving a nonsmooth convex optimization problem is proposed by combining Moreau‐Yosida regularization and bundle and quasi‐Newton ideas. In contrast with quasi‐Newton bundle methods of Mifflin et al. (1998), we only assume that the values of the objective function and its subgradients are evaluated approximately, which makes the method easier to implement. Under some reasonable assumptions, the proposed method is shown to have a Q‐superlinear rate of convergence.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2013/697474

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:697474

Access Statistics for this article

More articles in Abstract and Applied Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().