DocumentCode :
479756
Title :
Two Dimensions Simplex Evolution Algorithm
Author :
Hongfeng, Xiao ; Guanzheng, Tan
Author_Institution :
Dept. of Comput. Educ., Hunan Normal Univ., Changsha
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
313
Lastpage :
316
Abstract :
Under the basic frame of evolution computations (EA) and the kernel idea of Nelder-Mead simplex method, a novel evolution algorithm (EA), namely the two dimensions simplex EA (2D-simplexEA), is proposed. 2D-SimplexEA has four search operators: a reflection operator, a contraction operator, a plane search operator and a mutation operator. The first three operators and the forth operators are applied to the worst vertex and the best vertex respectively in order to reproduce a better vertex. The priority of the three operators for the worst vertex is the reflection operator, the contraction operator and the plane search operator, because there is a strong possibility that the reflection operator and the contraction operator can find out a new vertex better than the worst vertex along the optimal search direction of Nelder-Mead simplex method. When neither of them finds out a better vertex, the plane search operator is effective. It is the most important means for the best vertex to be improved by mutation without the other effective information and approaches. The numerical experiments verify 2D-SimplexEA correct and effective.
Keywords :
evolutionary computation; 2D simplex evolution algorithm; Nelder-Mead simplex method; contraction operator; evolution computations; mutation operator; optimal search direction; plane search operator; reflection operator; Computer science; Computer science education; Equations; Fuses; Genetic mutations; Information science; Kernel; Reflection; Software algorithms; Software engineering; Nelder-Mead simplex; evolution algorithm; low dimensions simplex; random search operator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.768
Filename :
4721750
Link To Document :
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