DocumentCode
3404935
Title
Comparing some graph crossover in genetic network programming
Author
Katagiri, Hironobu ; Hirasawa, Kotaro ; Hu, Jinglu ; Murata, Junichi
Author_Institution
Graduate Sch. of Inf. Sci & Electr. Eng.., Kyushu Univ., Japan
Volume
2
fYear
2002
fDate
5-7 Aug. 2002
Firstpage
1263
Abstract
In this paper, we studied the crossover for graph-based programs. The graph crossover is unsatisfactory on several counts to divide and combine graphs unlike with string or tree crossover, because a relatively large number of random factors should be inevitable to operate the crossover. In this paper, we compared the performance of several crossover operators for the genetic network programming experimentally. The experimental results show the advantages and drawbacks of each method.
Keywords
genetic algorithms; graph theory; genetic network programming; graph crossover; graph representation; graph-based evolutionary method; graph-based programs; random factors; Economic indicators; Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Information science; Intelligent networks; Search methods; Tail; Tree graphs;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE 2002. Proceedings of the 41st SICE Annual Conference
Print_ISBN
0-7803-7631-5
Type
conf
DOI
10.1109/SICE.2002.1195369
Filename
1195369
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