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231222s2002 xx ||||| 00| ||eng c |
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Cai, Wensheng
|e verfasserin
|4 aut
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| 245 |
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|a A fast annealing evolutionary algorithm for global optimization
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|c 2002
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 24.10.2002
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|a Date Revised 03.11.2003
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimization of test functions and a comparison of the algorithm with other stochastic optimization methods, it is shown that the algorithm is a highly efficient optimization method. It was also applied in optimization of Lennard-Jones clusters and compared with other methods in this study. The results indicate that the algorithm is a good tool for the energy minimization problem
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|a Journal Article
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| 700 |
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|a Shao, Xueguang
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 23(2002), 4 vom: 22. März, Seite 427-35
|w (DE-627)NLM098138448
|x 0192-8651
|7 nnns
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| 773 |
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|g volume:23
|g year:2002
|g number:4
|g day:22
|g month:03
|g pages:427-35
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