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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segre...

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Main Authors: Koh, Johnny Siaw Paw, Aris, Ishak, Ramachandaramurthy, Vigna Kumaran, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce
Format: Article
Language:English
English
Published: 2006
Online Access:http://psasir.upm.edu.my/id/eprint/18275/1/Design.pdf
http://psasir.upm.edu.my/id/eprint/18275/
http://dx.doi.org/10.3923/jas.2006.2201.2208
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spelling my.upm.eprints.182752015-09-28T08:43:31Z http://psasir.upm.edu.my/id/eprint/18275/ Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module Koh, Johnny Siaw Paw Aris, Ishak Ramachandaramurthy, Vigna Kumaran Bashi, Sinan Mahmod Marhaban, Mohammad Hamiruce This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. Also, proposed are the new modifications to existing crossover operator called DPPC (Dynamic Pre-Populated Crossover) together with modification of a simple crossover selection method, called BCS (Bi-Cycle Selection Method). The performance of the new operator called GA_INSP (GA Inspection Module) for a better evolutionary approach to the time-based problem has been discussed in the study. The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. © 2006 Asian Network for Scientific Information. 2006-08-30 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/18275/1/Design.pdf Koh, Johnny Siaw Paw and Aris, Ishak and Ramachandaramurthy, Vigna Kumaran and Bashi, Sinan Mahmod and Marhaban, Mohammad Hamiruce (2006) Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module. Journal of Applied Sciences, 6 (10). pp. 2201-2208. ISSN 1812-5654 http://dx.doi.org/10.3923/jas.2006.2201.2208 doi:10.3923/jas.2006.2201.2208 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. Also, proposed are the new modifications to existing crossover operator called DPPC (Dynamic Pre-Populated Crossover) together with modification of a simple crossover selection method, called BCS (Bi-Cycle Selection Method). The performance of the new operator called GA_INSP (GA Inspection Module) for a better evolutionary approach to the time-based problem has been discussed in the study. The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. © 2006 Asian Network for Scientific Information.
format Article
author Koh, Johnny Siaw Paw
Aris, Ishak
Ramachandaramurthy, Vigna Kumaran
Bashi, Sinan Mahmod
Marhaban, Mohammad Hamiruce
spellingShingle Koh, Johnny Siaw Paw
Aris, Ishak
Ramachandaramurthy, Vigna Kumaran
Bashi, Sinan Mahmod
Marhaban, Mohammad Hamiruce
Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
author_facet Koh, Johnny Siaw Paw
Aris, Ishak
Ramachandaramurthy, Vigna Kumaran
Bashi, Sinan Mahmod
Marhaban, Mohammad Hamiruce
author_sort Koh, Johnny Siaw Paw
title Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_short Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_full Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_fullStr Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_full_unstemmed Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_sort design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
publishDate 2006
url http://psasir.upm.edu.my/id/eprint/18275/1/Design.pdf
http://psasir.upm.edu.my/id/eprint/18275/
http://dx.doi.org/10.3923/jas.2006.2201.2208
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score 13.211869

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