- Title
- An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization
- Creator
- Bagirov, Adil; Ganjehlou, Asef Nazari
- Date
- 2008
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/64682
- Identifier
- vital:71
- Identifier
-
https://doi.org/10.1007/s00186-007-0186-5
- Identifier
- ISSN:1432-2994
- Abstract
- In this paper a new algorithm for minimizing locally Lipschitz functions is developed. Descent directions in this algorithm are computed by solving a system of linear inequalities. The convergence of the algorithm is proved for quasidifferentiable semismooth functions. We present the results of numerical experiments with both regular and nonregular objective functions. We also compare the proposed algorithm with two different versions of the subgradient method using the results of numerical experiments. These results demonstrate the superiority of the proposed algorithm over the subgradient method. © 2007 Springer-Verlag.; C1
- Publisher
- Springer-Verlag
- Relation
- Mathematical Methods of Operations Research Vol. 67, no. 2 (2008), p. 187-206; http://purl.org/au-research/grants/arc/DP0666061
- Rights
- Copyright Springer
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0102 Applied Mathematics; Nonsmooth optimization; Quasidifferentiable functions; Semismooth functions; Subdifferential; Function evaluation; Linear matrix inequalities; Optimisation; Algorithms
- Full Text
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