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Stochastic global optimization methods part I: Clustering methods |
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| Authors: | A. H. G. Rinnooy Kan G. T. Timmer |
| Affiliation: | (1) Department of Industrial Engineering and Operations Research/Graduate School of Business Administration, University of California, Berkeley, CA, USA;(2) Econometric Institute, Erasmus University Rotterdam, The Netherlands;(3) ORTEC Consultants, Rotterdam, The Netherlands |
| Abstract: | In this stochastic approach to global optimization, clustering techniques are applied to identify local minima of a real valued objective function that are potentially global. Three different methods of this type are described; their accuracy and efficiency are analyzed in detail. |
| Keywords: | Global optimization clustering sampling methods |
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