Multi-objective genetic algorithms in the study of the genetic code’s adaptability

Using a robustness measure based on values of the polar requirement of amino acids, Freeland and Hurst (1998) showed that less than one in one million random hypothetical codes are better than the standard genetic code. In this paper, instead of comparing the standard code with randomly generated co...

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Bibliographic Details

Published in:	Information sciences Vol. 425; pp. 48 - 61
Main Authors:	de Oliveira, Lariza Laura, Freitas, Alex A., Tinós, Renato
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.01.2018
Subjects:	Genetic algorithms Genetic code Lexicographic approach Multi-objective genetic algorithm Multi-objective genetic algorithm Genetic code Lexicographic approach Genetic algorithms
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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