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.
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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.
|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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