DNA Computing Based RNA Genetic Algorithm

Jili Tao (), Ridong Zhang () and Yong Zhu ()
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Jili Tao: NingboTech University, School of Information Science and Engineering
Ridong Zhang: Hangzhou Dianzi University, The Belt and Road Information Research Institute
Yong Zhu: NingboTech University, School of Information Science and Engineering

Chapter Chapter 2 in DNA Computing Based Genetic Algorithm, 2020, pp 25-55 from Springer

Abstract: Abstract Based on the biological RNA operations, DNA sequence selection, and mutation model, a RNA genetic algorithm (RNA-GA) algorithm is described in detail in this chapter. RNA molecules A, T, U, and C are utilized to encode the chromosome, and RNA molecular operations and DNA mutation model are combined to improve the crossover and mutation operators of SGA. The convergence of RNA-GA is analyzed using the Markov chain model. Five benchmark functions are applied to demonstrate the application process of the RNA-GA algorithm, and compare with SGA to effectively show the results by alleviating the premature convergence and improving the exploitation capacity of SGA.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-5403-2_2

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DOI: 10.1007/978-981-15-5403-2_2

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