Automatic Starting Point Selection For Function Optimization

Brooks, S.P. and Morgan, B.J.T. (1994) Automatic Starting Point Selection For Function Optimization. Statistics and Computing, 4 (3). pp. 173-177. ISSN 0960-3174. (The full text of this publication is not available from this repository)

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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
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: Faculties > Science Technology and Medical Studies > School of Computing > Theoretical Computing Group
Depositing User: P. Ogbuji
Date Deposited: 04 Jul 2009 07:15
Last Modified: 20 Apr 2012 13:49
Resource URI: http://kar.kent.ac.uk/id/eprint/20405 (The current URI for this page, for reference purposes)
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