- Title
- Aggregate subgradient method for nonsmooth DC optimization
- Creator
- Bagirov, Adil; Taheri, Sona; Joki, Kaisa; Karmitsa, Napsu; Mäkelä, Marko
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/175938
- Identifier
- vital:15031
- Identifier
-
https://doi.org/10.1007/s11590-020-01586-z
- Identifier
- ISBN:1862-4472 (ISSN)
- Abstract
- The aggregate subgradient method is developed for solving unconstrained nonsmooth difference of convex (DC) optimization problems. The proposed method shares some similarities with both the subgradient and the bundle methods. Aggregate subgradients are defined as a convex combination of subgradients computed at null steps between two serious steps. At each iteration search directions are found using only two subgradients: the aggregate subgradient and a subgradient computed at the current null step. It is proved that the proposed method converges to a critical point of the DC optimization problem and also that the number of null steps between two serious steps is finite. The new method is tested using some academic test problems and compared with several other nonsmooth DC optimization solvers. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- Optimization Letters Vol. 15, no. 1 (2021), p. 83-96; http://purl.org/au-research/grants/arc/DP190100580
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © Springer-Verlag GmbH Germany, part of Springer Nature 2020
- Subject
- 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; DC optimization; Nonconvex optimization; Nonsmooth optimization; Subgradient method
- Full Text
- Reviewed
- Funder
- This research by Dr. Adil Bagirov and Dr. Sona Taheri was supported by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (Project No. DP190100580). The research by Dr. Napsu Karmitsa and Dr. Sona Taheri was supported by the Academy of Finland (Projects Nos. 289500 and 319274).
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