DocumentCode
626843
Title
Genetic Algorithm with virus infection for finding approximate solution
Author
Inoue, Takeru ; Uwate, Yoko ; Nishio, Yusuke
Author_Institution
Tokushima Univ., Tokushima, Japan
fYear
2013
fDate
19-23 May 2013
Firstpage
1604
Lastpage
1607
Abstract
Genetic Algorithm (GA) is modeling behavior of evolution in organic and known as one of method to solve Traveling Salesman Problem (TSP). However, GA obtains solution by overlaying generations because of being based on evolution in organic. Thus, it takes a long time to find approximate solution. While, Virus Theory of Evolution (VTE) can evolve by virus infection. VTE characteristic has sharing of information among same generation. If new algorithm is using both these characteristics of GA and VTE, convergence speed would be faster than GA. Thus, this study proposes Genetic Algorithm with Virus Infection (GAVI). GAVI algorithm is Virus Theory of Evolution (VTE) to be based on Genetic Algorithm (GA). We apply GAVI to TSP and confirm that GAVI obtains more effective result than GA.
Keywords
genetic algorithms; travelling salesman problems; GAVI algorithm; TSP; VTE characteristic; approximate solution; convergence speed; evolution modeling behavior; genetic algorithm-virus infection algorithm; traveling salesman problem; virus theory-of-evolution; Approximation algorithms; Cities and towns; Convergence; Error analysis; Genetic algorithms; Genetics; Organisms;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location
Beijing
ISSN
0271-4302
Print_ISBN
978-1-4673-5760-9
Type
conf
DOI
10.1109/ISCAS.2013.6572168
Filename
6572168
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