A Human Community-Based Genetic Algorithm Model (HCBGA)

Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai pen...

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Main Author: Al-Madi, Nagham Azmi Qasim
Format: Thesis
Language:English
Published: 2009
Subjects:
Online Access:http://eprints.usm.my/41558/
http://eprints.usm.my/41558/1/Nagham_Azmi_Qasim_Al-Madi24.pdf
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author Al-Madi, Nagham Azmi Qasim
author_facet Al-Madi, Nagham Azmi Qasim
author_sort Al-Madi, Nagham Azmi Qasim
building USM Institutional Repository
collection Online Access
description Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai penyelidik terkini telah menggunakan populasi berstruktur dalam GA untuk mengurangkan kerawakan seperti model algoritma genetik pulau (IGA), model algoritma genetik bersel (CGA) dan model lain. As a general search model, Genetic Algorithm (GA) has proved its success in many applications. However, several researchers argue that GA has slow convergence. This shortfall is due to the randomness in most of its operations. Hence, recently researches have employed structured populations in GA to reduce this randomness, such as in the island genetic algorithm model (IGA), cellular genetic algorithm model (CGA) and other models.
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format Thesis
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institution Universiti Sains Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T17:45:21Z
publishDate 2009
recordtype eprints
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spelling usm-415582019-04-12T05:26:59Z http://eprints.usm.my/41558/ A Human Community-Based Genetic Algorithm Model (HCBGA) Al-Madi, Nagham Azmi Qasim QA75.5-76.95 Electronic computers. Computer science Sebagai satu model gelintaran, Algoritma Genetik (GA), telah membuktikan kejayaannya dalam banyak apikasi. Walau bagaimanapun, beberapa penyelidik menyatakan bahawa GA mempunyai “convergence” yang perlahan. Keperlahanan ini berpunca daripada kerawakan dalam kebanyakan operasinya. Oleh itu, ramai penyelidik terkini telah menggunakan populasi berstruktur dalam GA untuk mengurangkan kerawakan seperti model algoritma genetik pulau (IGA), model algoritma genetik bersel (CGA) dan model lain. As a general search model, Genetic Algorithm (GA) has proved its success in many applications. However, several researchers argue that GA has slow convergence. This shortfall is due to the randomness in most of its operations. Hence, recently researches have employed structured populations in GA to reduce this randomness, such as in the island genetic algorithm model (IGA), cellular genetic algorithm model (CGA) and other models. 2009-11 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/41558/1/Nagham_Azmi_Qasim_Al-Madi24.pdf Al-Madi, Nagham Azmi Qasim (2009) A Human Community-Based Genetic Algorithm Model (HCBGA). PhD thesis, Universiti Sains Malaysia.
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Al-Madi, Nagham Azmi Qasim
A Human Community-Based Genetic Algorithm Model (HCBGA)
title A Human Community-Based Genetic Algorithm Model (HCBGA)
title_full A Human Community-Based Genetic Algorithm Model (HCBGA)
title_fullStr A Human Community-Based Genetic Algorithm Model (HCBGA)
title_full_unstemmed A Human Community-Based Genetic Algorithm Model (HCBGA)
title_short A Human Community-Based Genetic Algorithm Model (HCBGA)
title_sort human community-based genetic algorithm model (hcbga)
topic QA75.5-76.95 Electronic computers. Computer science
url http://eprints.usm.my/41558/
http://eprints.usm.my/41558/1/Nagham_Azmi_Qasim_Al-Madi24.pdf