- Title
- Solving minimax problems : Local smoothing versus global smoothing
- Creator
- Bagirov, Adil; Sultanova, Nargiz; Al Nuaimat, Alia; Taheri, Sona
- Date
- 2018
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/165615
- Identifier
- vital:13274
- Identifier
-
https://doi.org/10.1007/978-3-319-90026-1_2
- Identifier
- ISBN:2194-1009 (ISSN); 978-331990025-4 (ISBN)
- Abstract
- The aim of this chapter is to compare different smoothing techniques for solving finite minimax problems. We consider the local smoothing technique which approximates the function in some neighborhood of a point of nondifferentiability and also global smoothing techniques such as the exponential and hyperbolic smoothing which approximate the function in the whole domain. Computational results on the collection of academic test problems are used to compare different smoothing techniques. Results show the superiority of the local smoothing technique for convex problems and global smoothing techniques for nonconvex problems. © 2018, Springer International Publishing AG, part of Springer Nature.; Springer Proceedings in Mathematics and Statistics
- Publisher
- Springer New York LLC
- Relation
- 4th International Conference on Numerical Analysis and Optimization, NAO-IV 2017; Muscat, Oman; 2nd-5th January 2017; published in Numerical Analysis and Optimization NAO-IV (part of the Springer Proceedings in Mathematics and Statistics book series PROMS, volume 235) Vol. 235, p. 23-43
- Rights
- Copyright © Springer International Publishing AG, part of Springer Nature 2018
- Rights
- This metadata is freely available under a CCO license
- Subject
- Minimax problems; Nonlinear programming; Nonsmooth optimization; Smoothing techniques
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