- Title
- An augmented subgradient method for minimizing nonsmooth DC functions
- Creator
- Bagirov, Adil; Hoseini Monjezi, Najmeh; Taheri, Sona
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/179063
- Identifier
- vital:15488
- Identifier
-
https://doi.org/10.1007/s10589-021-00304-4
- Identifier
- ISBN:0926-6003 (ISSN)
- Abstract
- A method, called an augmented subgradient method, is developed to solve unconstrained nonsmooth difference of convex (DC) optimization problems. At each iteration of this method search directions are found by using several subgradients of the first DC component and one subgradient of the second DC component of the objective function. The developed method applies an Armijo-type line search procedure to find the next iteration point. It is proved that the sequence of points generated by the method converges to a critical point of the unconstrained DC optimization problem. The performance of the method is demonstrated using academic test problems with nonsmooth DC objective functions and its performance is compared with that of two general nonsmooth optimization solvers and five solvers specifically designed for unconstrained DC optimization. Computational results show that the developed method is efficient and robust for solving nonsmooth DC optimization problems. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
- Publisher
- Springer
- Relation
- Computational Optimization and Applications Vol. 80, no. 2 (2021), p. 411-438; 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 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021
- Subject
- 0102 Applied Mathematics; 0103 Numerical and Computational Mathematics; DC optimization; Nonconvex optimization; Nonsmooth optimization; Subgradients
- Reviewed
- Funder
- The research by Dr. A.M. Bagirov is supported by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (Project No. DP190100580) and the research by Dr. N. Hoseini Monjezi is supported by the National Elite Foundation of Iran.
- Hits: 4035
- Visitors: 3782
- Downloads: 0
Thumbnail | File | Description | Size | Format |
---|