Liu, W.B. and Dai, Y. and Lamb, J.D. (2003) Novel Supervisor-Searcher Cooperation Algorithms For Minimization Problems With Strong Noise. Optimization Methods and Software, 18 (3). pp. 246-264. ISSN 1055-6788 .
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| Official URL http://dx.doi.org/10.1080/1055678031000119364 |
Abstract
This work continues the investigation in Ref. [1]: designing minimization algorithms in the framework of supervisor and searcher cooperation (SSC). It explores a wider range of possible supervisors and search engines to be used in the construction of SSC algorithms. Global convergence is established for algorithms with general supervisors and search engines in the absence of noise, and the convergence rate is studied. Both theoretical analysis and numerical results illustrate the appealing attributes of the proposed algorithms
| Item Type: | Article |
|---|---|
| Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
| Divisions: | Faculties > Social Sciences > Kent Business School |
| Depositing User: | Steve Wenbin Liu |
| Date Deposited: | 11 Sep 2008 13:05 |
| Last Modified: | 14 Jan 2010 14:31 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/8489 (The current URI for this page, for reference purposes) |
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