Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers
This study aims at designing an online adaptive method to control multiple parameters of the Genetic Algorithm. The efficiency of Genetic Algorithm requires maintaining an appropriate balance between exploration and exploitation, which in turn greatly depends on the settings of several parameters...
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my-usm-ep.413342018-08-16T02:46:15Z Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers 2010 Ghallab, Abdullatif Saleh Nasser RS1-441 Pharmacy and materia medica This study aims at designing an online adaptive method to control multiple parameters of the Genetic Algorithm. The efficiency of Genetic Algorithm requires maintaining an appropriate balance between exploration and exploitation, which in turn greatly depends on the settings of several parameters. The parameters are not independent and have complex interactions with each other during a given run. Ignoring the interaction between the adapted parameters or adapting one single parameter may have negative impact on the other related parameters, resulting in poor performance. However, most of the available alternatives cannot solve this problem effectively. Fuzzy Adaptive Genetic Algorithm techniques have been used recently for parameter control, 2010 Thesis http://eprints.usm.my/41334/ http://eprints.usm.my/41334/1/ABDULLATIF_SALEH_NASSER_GHALLAB.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Farmasi |
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English |
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RS1-441 Pharmacy and materia medica |
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RS1-441 Pharmacy and materia medica Ghallab, Abdullatif Saleh Nasser Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers |
description |
This study aims at designing an online adaptive method to control multiple parameters of the
Genetic Algorithm. The efficiency of Genetic Algorithm requires maintaining an appropriate
balance between exploration and exploitation, which in turn greatly depends on the settings of
several parameters. The parameters are not independent and have complex interactions with each
other during a given run. Ignoring the interaction between the adapted parameters or adapting
one single parameter may have negative impact on the other related parameters, resulting in poor
performance. However, most of the available alternatives cannot solve this problem effectively.
Fuzzy Adaptive Genetic Algorithm techniques have been used recently for parameter control, |
format |
Thesis |
qualification_name |
Doctor of Philosophy (PhD.) |
qualification_level |
Doctorate |
author |
Ghallab, Abdullatif Saleh Nasser |
author_facet |
Ghallab, Abdullatif Saleh Nasser |
author_sort |
Ghallab, Abdullatif Saleh Nasser |
title |
Simultaneous Adaptation Of Multiple
Genetic Algorithm Parameters Using Fuzzy
Logic Controllers
|
title_short |
Simultaneous Adaptation Of Multiple
Genetic Algorithm Parameters Using Fuzzy
Logic Controllers
|
title_full |
Simultaneous Adaptation Of Multiple
Genetic Algorithm Parameters Using Fuzzy
Logic Controllers
|
title_fullStr |
Simultaneous Adaptation Of Multiple
Genetic Algorithm Parameters Using Fuzzy
Logic Controllers
|
title_full_unstemmed |
Simultaneous Adaptation Of Multiple
Genetic Algorithm Parameters Using Fuzzy
Logic Controllers
|
title_sort |
simultaneous adaptation of multiple
genetic algorithm parameters using fuzzy
logic controllers |
granting_institution |
Universiti Sains Malaysia |
granting_department |
Pusat Pengajian Sains Farmasi |
publishDate |
2010 |
url |
http://eprints.usm.my/41334/1/ABDULLATIF_SALEH_NASSER_GHALLAB.pdf |
_version_ |
1747820913783472128 |