Introduction of a sectioned genetic algorithm for large scale problems

The sectioned genetic algorithm (hereafter denoted as sectioned GA), which is presented in this paper, represents a modification of the standard GA and deals with large scale problems (i.e. problems involving pattern spaces with high dimensionalities). Instead of increasing the size of the populatio...

Full description

Saved in:
Bibliographic Details
Published in:2007 2nd Bio-Inspired Models of Network, Information and Computing Systems pp. 2 - 7
Main Authors: Detorakis, Z., Tambouratzis, G.
Format: Conference Proceeding
Language:English
Published: IEEE 2007
Subjects:
Gallium
Genetic algorithms
Genetics
Histograms
input space dimensionality
masks
parallel distributed algorithms
Program processors
Speech processing
stemming
Training
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract The sectioned genetic algorithm (hereafter denoted as sectioned GA), which is presented in this paper, represents a modification of the standard GA and deals with large scale problems (i.e. problems involving pattern spaces with high dimensionalities). Instead of increasing the size of the population searching the pattern space when the problem dimensionality increases, the sectioned GA approach divides each individual into smaller parts (sections) and subsequently applies the genetic operators on each of these parts. Results from the application of sectioned GA on the problem of automatic morphological analysis are also presented in this article. Morphological analysis is by nature a large scale problem since a great number of words need to be segmented into stems and suffixes. The proposed system improves the segmentation accuracy substantially in comparison to standard GA algorithms.
AbstractList The sectioned genetic algorithm (hereafter denoted as sectioned GA), which is presented in this paper, represents a modification of the standard GA and deals with large scale problems (i.e. problems involving pattern spaces with high dimensionalities). Instead of increasing the size of the population searching the pattern space when the problem dimensionality increases, the sectioned GA approach divides each individual into smaller parts (sections) and subsequently applies the genetic operators on each of these parts. Results from the application of sectioned GA on the problem of automatic morphological analysis are also presented in this article. Morphological analysis is by nature a large scale problem since a great number of words need to be segmented into stems and suffixes. The proposed system improves the segmentation accuracy substantially in comparison to standard GA algorithms.
Author Tambouratzis, G.
Detorakis, Z.
Author_xml – sequence: 1
  givenname: Z.
  surname: Detorakis
  fullname: Detorakis, Z.
  organization: Inst. for Language & Speech Process., Athens
– sequence: 2
  givenname: G.
  surname: Tambouratzis
  fullname: Tambouratzis, G.
  organization: Inst. for Language & Speech Process., Athens
BookMark eNotj7FOwzAUAI0EA5R-AQz-gRT7OY7jESJKIxUY6F692M_BUhJXThj4exB0Ot1y0t2wyylNxNi9FBsphX14al_f2uZjA0KYTVnJX8AFW1tT20pZY63Q9ppt22nJyX-5JaaJp8CRz_Qn5HlPEy3RcRz6lOPyOfKQMh8w98RnhwPxU07dQON8y64CDjOtz1yxw_b50OyK_ftL2zzuiyhBLgV61KaUtYJOCV8HKpUDaTog753THozWXgFCqFBbAu2ASBqUNojgtFqxu_9sJKLjKccR8_fxPKd-ANYxSjk
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/BIMNICS.2007.4610072
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9789639799059
963979905X
EndPage 7
ExternalDocumentID 4610072
Genre orig-research
GroupedDBID 6IE
6IL
CBEJK
RIE
RIL
ID FETCH-LOGICAL-i121t-ada5741832b30d8fe43c217b2eddcc5d2755d32a2f6a59e25c2ee17a19f0fc53
IEDL.DBID RIE
IngestDate Thu Jun 29 18:17:52 EDT 2023
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i121t-ada5741832b30d8fe43c217b2eddcc5d2755d32a2f6a59e25c2ee17a19f0fc53
PageCount 6
ParticipantIDs ieee_primary_4610072
PublicationCentury 2000
PublicationDate 2007-00-00
PublicationDateYYYYMMDD 2007-01-01
PublicationDate_xml – year: 2007
  text: 2007-00-00
PublicationDecade 2000
PublicationTitle 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems
PublicationTitleAbbrev BIMNICS
PublicationYear 2007
Publisher IEEE
Publisher_xml – name: IEEE
Score 1.379721
Snippet The sectioned genetic algorithm (hereafter denoted as sectioned GA), which is presented in this paper, represents a modification of the standard GA and deals...
SourceID ieee
SourceType Publisher
StartPage 2
SubjectTerms Gallium
Genetic algorithms
Genetics
Histograms
input space dimensionality
masks
parallel distributed algorithms
Program processors
Speech processing
stemming
Training
Title Introduction of a sectioned genetic algorithm for large scale problems
URI https://ieeexplore.ieee.org/document/4610072
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEB5q8eBJpRXf5ODRtZtks0muFos9uBTsobeSzUMLtZVu6-93srtUBC_eQgh5P2Ym830DcBdEiVK0RN0EpYEk04onSmQyEU673ATuuSvrYBOyKNRspicduN9jYbz3tfOZf4jJ-i_fre0umsoGkRs8lXjhHkiZN1itFg1HUz14HL8U4-FrQ0vYFv0VM6V-MkbH_2vsBPo_2Dsy2b8qp9Dxqx6MxtGh3DVMr2QdiCFV7UOFlyTBLRCRiMQs39ao6r9_EBREyTK6eJMKl8CTNmpM1Yfp6Gk6fE7aCAjJgjK6TYwzItLLcFby1KngM25RhyiZd85a4ZgUwnFmWMiN0J4Jy7yn0lAd0mAFP4PuCntyDsTYFOtRQlo8FcYazVKJVdBSSW4VzS-gF6dg_tlwXMzb0V_-nX0FR42NM5oirqG73ez8DRzar-2i2tzWC_MNG2SRRA
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4ImuhJDRjf9uDRlT62tL1KJGyEDYkcuJFu21USBMKCv9_p7gZj4sVb0zR9P2am832D0EMuMpCiJegmIA1EsVY8UiKWkXDadU3OPXdZGWxCpqmaTvW4gR73WBjvfel85p9CsvzLdyu7C6ayTuAGJxIu3AMRx4xUaK0aD0eJ7jwnozTpvVXEhHXhX1FTykejf_K_5k5R-wd9h8f7d-UMNfyyhfpJcCl3FdcrXuXY4KL0ooJrEsMmCFhEbBbvK1D2Pz4xiKJ4EZy8cQGL4HEdN6Zoo0n_ZdIbRHUMhGhOGd1GxhkRCGY4yzhxKvcxt6BFZMw7Z61wTArhODMs7xqhPROWeU-loTonuRX8HDWX0JMLhI0lUI8S0sK5MNZoRiRUQTMluVW0e4laYQpm64rlYlaP_urv7Ht0NJiMhrNhkr5eo-PK4hkMEzeoud3s_C06tF_bebG5KxfpG9jslIs
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2007+2nd+Bio-Inspired+Models+of+Network%2C+Information+and+Computing+Systems&rft.atitle=Introduction+of+a+sectioned+genetic+algorithm+for+large+scale+problems&rft.au=Detorakis%2C+Z.&rft.au=Tambouratzis%2C+G.&rft.date=2007-01-01&rft.pub=IEEE&rft.spage=2&rft.epage=7&rft_id=info:doi/10.1109%2FBIMNICS.2007.4610072&rft.externalDocID=4610072