Brooks, Stephen P., Morgan, Byron J. T. (1994) Automatic Starting Point Selection For Function Optimization. Statistics and Computing, 4 (3). pp. 173-177. ISSN 0960-3174. (doi:10.1007/bf00142569) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:20405)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: https://doi.org/10.1007/bf00142569 |
|
Abstract
Traditional (non-stochastic) iterative methods for optimizing functions with multiple optima require a good procedure for selecting starting points. This paper illustrates how the selection of starting points can be made automatically by using a method based upon simulated annealing. We present a hybrid algorithm, possessing the accuracy of traditional routines, whilst incorporating the reliability of annealing methods, and illustrate its performance for a particularly complex practical problem.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1007/bf00142569 |
| Uncontrolled keywords: | MAXIMUM LIKELIHOOD; MIXTURE MODELS; SIMULATED ANNEALING; OPTIMIZATION; HYBRID ALGORITHM |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
| Institutional Unit: | Schools > School of Computing |
| Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
|
| Depositing User: | P. Ogbuji |
| Date Deposited: | 04 Jul 2009 07:15 UTC |
| Last Modified: | 20 May 2025 10:06 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/20405 (The current URI for this page, for reference purposes) |
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