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Automatic Starting Point Selection For Function Optimization

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
Divisions: 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: 09 Mar 2023 11:31 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/20405 (The current URI for this page, for reference purposes)

University of Kent Author Information

Morgan, Byron J. T..

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