- Title
- Global minimizer of large scale stochastic rosenbrock function : canonical duality approach
- Creator
- Li, Chaojie; Gao, David
- Date
- 2012
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/67863
- Identifier
- vital:4857
- Identifier
-
https://doi.org/10.1007/978-3-642-34478-7_82
- Identifier
- ISBN:03029743 (ISSN); 9783642344770 (ISBN)
- Abstract
- Canonical duality theory for solving the well-known benchmark test problem of stochastic Rosenbrock function is explored by two canonical transformations. Global optimality criterion is analytically obtained, which shows that the stochastic disturbance of these parameters could be eliminated by a proper canonical dual transformation. Numerical simulations illustrate the canonical duality theory is potentially powerful for solving this benchmark test problem and many other challenging problems in global optimization and complex network systems. © 2012 Springer-Verlag.
- Publisher
- Doha Springer Berlin Heidelberg
- Relation
- 19th International Conference on Neural Information Processing, ICONIP 2012 Vol. 7666 LNCS, p. 677-682
- Rights
- Copyright 2012 Springer-Verlag
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Canonical Duality Theory; Global Optimation; Stochastic Rosenbrock Function; Benchmark test problem; Canonical transformation; Complex network systems; Dual transformation; Global minimizers; Stochastic disturbances; Benchmarking; Data processing; Global optimization; Stochastic systems
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Accepted version | 9 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | SOURCE2 | Published Version | 2 MB | Adobe Acrobat PDF | View Details Download |