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Extending the Scalability of Linkage Learning Genetic Algorithms Book

Extending the Scalability of Linkage Learning Genetic Algorithms
Extending the Scalability of Linkage Learning Genetic Algorithms, , Extending the Scalability of Linkage Learning Genetic Algorithms has a rating of 3.5 stars
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Extending the Scalability of Linkage Learning Genetic Algorithms, , Extending the Scalability of Linkage Learning Genetic Algorithms
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  • Extending the Scalability of Linkage Learning Genetic Algorithms
  • Written by author Ying-ping Chen
  • Published by Springer-Verlag New York, LLC, June 2009
  • Genetic algorithms (GAs) are powerful search techniques based on principles of evolution and widely applied to solve problems in many disciplines. However, most GAs employed in practice nowadays are unable to learn genetic linkage and suffer from the link
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Book Categories

Authors

1Introduction1
2Genetic algorithms and genetic linkage5
3Genetic linkage learning techniques23
4Linkage learning genetic algorithm35
5Preliminaries : assumptions and the test problem45
6A first improvement : using promoters51
7Convergence time for the linkage learning genetic algorithm63
8Introducing subchromosome representations91
9Conclusions101


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