- Title
- Comparing different nonsmooth minimization methods and software
- Creator
- Karmitsa, Napsu; Bagirov, Adil; Makela, Marko
- Date
- 2012
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/60726
- Identifier
- vital:4550
- Identifier
-
https://doi.org/10.1080/10556788.2010.526116
- Identifier
- ISSN:1055-6788
- Abstract
- Most nonsmooth optimization (NSO) methods can be divided into two main groups: subgradient methods and bundle methods. In this paper, we test and compare different methods from both groups as well as some methods which may be considered as hybrids of these two and/or some others. All the solvers tested are so-called general black box methods which, at least in theory, can be applied to solve almost all NSO problems. The test set includes a large number of unconstrained nonsmooth convex and nonconvex problems of different size. In particular, it includes piecewise linear and quadratic problems. The aim of this work is not to foreground some methods over the others but to get some insight on which method to select for certain types of problems. © 2012 Taylor and Francis Group, LLC.
- Relation
- Optimization Methods and Software Vol. 27, no. 1 (2012), p. 131-153; http://purl.org/au-research/grants/arc/DP0666061
- Rights
- Taylor and Francis Group, LLC.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Numerical performance; Subgradient methods; Black box method; Bundle methods; Different sizes; Main group; Minimization methods; Non-differentiable optimization; Non-smooth; Nonconvex problem; Nonsmooth optimization; Piecewise linear; Quadratic problem; Test sets; Optimization; Piecewise linear techniques; Numerical methods
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