DocumentCode
2913625
Title
Improving the performance of LZWGA by using a new mutation method
Author
Numnark, Somrak ; Suwannik, Worasait
Author_Institution
Fac. of Sci., Kasetsart Univ., Bangkok
fYear
2008
fDate
1-6 June 2008
Firstpage
1862
Lastpage
1865
Abstract
LZW encoding in Genetic Algorithm (LZWGA) encodes a chromosome in a format that can be decompressed by Lempel-Ziv-Welch (LZW) algorithm. This encoding reduces the size of the chromosome and enabled the algorithm to solve a very large problem. This paper proposes a novel mutation in LZWGA. The result shows that the new method can solve OneMax and Trap problem 46.3% faster. Moreover, this method can reduce the size of the compressed chromosome by 54.8%.
Keywords
encoding; genetic algorithms; Lempel-Ziv-Welch algorithm; Lempel-Ziv-Welch encoding; compressed chromosome; genetic algorithm; mutation method; Algorithm design and analysis; Compression algorithms; Data compression; Data structures; Dictionaries; Evolutionary computation; Genetic mutations; Heuristic algorithms; Resists; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631042
Filename
4631042
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