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A Structured-Population Genetic-Algorithm based on Hierarchical Hypercube of Genes Expressions

by Mohamed A. Belal, Mohamed H. Haggag
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 22
Year of Publication: 2013
Authors: Mohamed A. Belal, Mohamed H. Haggag
10.5120/10775-4446

Mohamed A. Belal, Mohamed H. Haggag . A Structured-Population Genetic-Algorithm based on Hierarchical Hypercube of Genes Expressions. International Journal of Computer Applications. 64, 22 ( February 2013), 5-18. DOI=10.5120/10775-4446

@article{ 10.5120/10775-4446,
author = { Mohamed A. Belal, Mohamed H. Haggag },
title = { A Structured-Population Genetic-Algorithm based on Hierarchical Hypercube of Genes Expressions },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 22 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number22/10775-4446/ },
doi = { 10.5120/10775-4446 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:17:18.073967+05:30
%A Mohamed A. Belal
%A Mohamed H. Haggag
%T A Structured-Population Genetic-Algorithm based on Hierarchical Hypercube of Genes Expressions
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 22
%P 5-18
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Structured-population Genetic Algorithm (GA) usually leads to more superior performance than the panmictic genetic algorithm; since it can control two opposite processes, namely exploration and exploitation in the search space. Several spatially structured-population GAs have been introduced in the literature such as cellular, patchwork, island-model, terrain-based A, graph-based, religion-based and social-based GA. All the aforementioned works did not construct the sub-populations based on the genes information of the individuals themselves. The structuring of sub-populations based on this information might help in attaining better performance and more efficient search strategy. In this paper, the structured population is represented as hierarchical hypercube of sub-populations that are dynamically constructed and adapted at search time. Each sub-population represents a sub-division of the real genes space. This structure could help in directing the search towards the promising sub-spaces. Finally, a comparative study with other known structured population GA is provided.

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Index Terms

Computer Science
Information Sciences

Keywords

Evolutionary Algorithms Genetic Algorithms Structured Population Gene Expression

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