- Title
- Subgradient smoothing method for nonsmooth nonconvex optimization
- Creator
- Bagirov, Adil; Sultanova, Nargiz; Taheri, Sona; Ozturk, Gurkan
- Date
- 2021
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/183592
- Identifier
- vital:16309
- Identifier
-
https://doi.org/10.1007/978-3-030-72040-7_3
- Identifier
- ISBN:21941009 (ISSN); 9783030720391 (ISBN)
- Abstract
- In this chapter an unconstrained nonsmooth nonconvex optimization problem is considered and a method for solving this problem is developed. In this method the subproblem for finding search directions is reduced to the unconstrained minimization of a smooth function. This is achieved by using subgradients computed in some neighborhood of a current iteration point and by formulating the search direction finding problem to the minimization of the convex piecewise linear function over the unit ball. The hyperbolic smoothing technique is applied to approximate the minimization problem by a sequence of smooth problems. The convergence of the proposed method is studied and its performance is evaluated using a set of nonsmooth optimization academic test problems. In addition, the method is implemented in GAMS and numerical results using different solvers from GAMS are reported. The proposed method is compared with a number of nonsmooth optimization methods. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Publisher
- Springer
- Relation
- 5th International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer, NAOV, Muscan, 6-9 January 2020 Vol. 354, p. 57-79
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Subject
- Nonconvex optimization; Nonsmooth optimization; Smoothing techniques; Subdifferential mapping
- Reviewed
- Funder
- Australian Research Council’s Discovery Projects funding scheme (Project No. DP19000580) and partially by the Academy of Finland (Project No. 319274).
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