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Optimization Algorithm using Evolutionary Process of DNA with Introns

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  033095,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14054) @2003
Authors:   Hiroshi Kitabata, Tsuyoshi Okayama, Sachi Uemura, Katsusuke Murakami, Haruhiko Murase
Keywords:   bio system derived, genetic algorithms, computer

Recently, genetic algorithms (GAs) have received a lot of attention because of their easy-to-use features for solving many engineering problems. They are capable of locating a good approximate in extremely large search spaces with a reasonable amount of computational effort. In this study, we have developed the DNA algorithms (DNAAs). The distinction between GAs and DNAAs originates from the fact that GAs take into account only exons whereas on the other hand DNAAs take into account not only exons but also introns. Intron is an intervening sequence that does not have genetic information, and exon is a structural sequence that is used to construct protein. Advanced animals such as human beings have a 90% or higher percentage of introns in their DNA sequences, while lower organisms have a smaller percentage of introns in their DNA sequences. In the process of transferring gene information from one generation to another, the correctness of the genetic information can be maintained by holding the useless information together with the important information. Living things have developed such genetic redundancy in the process of their evolution to avoid the unfavorable effects of mutation. We investigated the role of introns and the performance of the DNAAs by solving a string search problem and a knapsack problem by the DNAAs. As a result, DNAAs showed a firm robustness for a fairly high ratio of mutation. It was also found that more introns were accumulated near exons whose role seems more important than other exons.

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