NDLI: A novel tree differential evolution using inter-symbol distance

Content Provider	IEEE Xplore Digital Library
Author	Kushida, J.-I. Hara, A. Takahama, T.
Copyright Year	2014
Description	Author affiliation: Grad. Sch. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan (Kushida, J.-I.; Hara, A.; Takahama, T.)
Abstract	Differential Evolution (DE) is one of the evolutionary algorithm that was developed to handle optimization problems over continuous domains. It's a population-based stochastic search technique with simple concept and high efficient. In recent year, many DE variants were proposed and have been applied for solving various problems. In addition, some DE based techniques are modified to handle discrete optimization problems. One of them, Tree based DE (TreeDE), which maps full trees to vectors and represents discrete symbols by points in a real-valued vector space, is a new DE-based tree discovering algorithm. TreeDE directly can apply differential operation of DE to individual vectors. However, since the search space of genotypes in the TreeDE does not correspond to the solution space of phenotypes (program tree), the mutation operation will not always work effectively. Therefore, we explicitly handle the distance of programming tree and propose new TreeDE which optimizes tree structure based on DE. In the proposed method, each individual has two types of genes: one express the neighborhood structure between the symbols, the other represents a full tree structure of the program. By evolving both genes simultaneously, effective mutation operation and optimization of the tree structure by DE engine are realized. The proposed TreeDE is compared with Genetic Programming (GP) on standard benchmark problems, and experimental results showed the effectiveness of the proposed TreeDE.
Starting Page	107
Ending Page	112
File Size	677796
Page Count	6
File Format	PDF
ISBN	9781479947713
ISSN	18833977
e-ISBN	9781479947706
DOI	10.1109/IWCIA.2014.6988087
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-07
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sociology Differential Evolution Linear programming Vectors Genetic Programming Statistics Regression tree analysis Optimization Standards Inter-symbol Distance
Content Type	Text
Resource Type	Article

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