Path optimization using genetic algorithm in laser scanning system

Laser marking is superior in quality and flexibility to conventional marking techniques such as ink stamping marking. The beam deflected scanning has been commonly applied in the industries. In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortenin...

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Main Authors: Chen C.P., Koh S.P., Aris I.B., Albert F.Y.C., Tiong S.K.
Other Authors: 25824552100
Format: Conference paper
Published: 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-297192023-12-28T15:41:47Z Path optimization using genetic algorithm in laser scanning system Chen C.P. Koh S.P. Aris I.B. Albert F.Y.C. Tiong S.K. 25824552100 22951210700 6603306751 56572305600 15128307800 Diesel engines Genetic algorithms Information technology Laser applications Lasers Convergent speeds Cross overs Dynamic variables Laser markings Number representations Path optimizations Real-coded genetic algorithms Scanning paths Scanning systems Sequencing problems Simulation results Two points Scanning Laser marking is superior in quality and flexibility to conventional marking techniques such as ink stamping marking. The beam deflected scanning has been commonly applied in the industries. In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. The GA would base on the real-number representation, namely Real-Coded Genetic Algorithm (RCGA). It employs the Dynamic Variable Length Two Point Crossover (DVL-2PC). The simulation results indicating that the proposed algorithm has good convergent speed and manage to solve the sequencing problem efficiently. � 2008 IEEE. Final 2023-12-28T07:41:47Z 2023-12-28T07:41:47Z 2008 Conference paper 10.1109/ITSIM.2008.4632037 2-s2.0-57349152411 https://www.scopus.com/inward/record.uri?eid=2-s2.0-57349152411&doi=10.1109%2fITSIM.2008.4632037&partnerID=40&md5=6a4dd243cc64e31b1b9be89e43abf500 https://irepository.uniten.edu.my/handle/123456789/29719 4 4632037 All Open Access; Green Open Access Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Diesel engines
Genetic algorithms
Information technology
Laser applications
Lasers
Convergent speeds
Cross overs
Dynamic variables
Laser markings
Number representations
Path optimizations
Real-coded genetic algorithms
Scanning paths
Scanning systems
Sequencing problems
Simulation results
Two points
Scanning
spellingShingle Diesel engines
Genetic algorithms
Information technology
Laser applications
Lasers
Convergent speeds
Cross overs
Dynamic variables
Laser markings
Number representations
Path optimizations
Real-coded genetic algorithms
Scanning paths
Scanning systems
Sequencing problems
Simulation results
Two points
Scanning
Chen C.P.
Koh S.P.
Aris I.B.
Albert F.Y.C.
Tiong S.K.
Path optimization using genetic algorithm in laser scanning system
description Laser marking is superior in quality and flexibility to conventional marking techniques such as ink stamping marking. The beam deflected scanning has been commonly applied in the industries. In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. The GA would base on the real-number representation, namely Real-Coded Genetic Algorithm (RCGA). It employs the Dynamic Variable Length Two Point Crossover (DVL-2PC). The simulation results indicating that the proposed algorithm has good convergent speed and manage to solve the sequencing problem efficiently. � 2008 IEEE.
author2 25824552100
author_facet 25824552100
Chen C.P.
Koh S.P.
Aris I.B.
Albert F.Y.C.
Tiong S.K.
format Conference paper
author Chen C.P.
Koh S.P.
Aris I.B.
Albert F.Y.C.
Tiong S.K.
author_sort Chen C.P.
title Path optimization using genetic algorithm in laser scanning system
title_short Path optimization using genetic algorithm in laser scanning system
title_full Path optimization using genetic algorithm in laser scanning system
title_fullStr Path optimization using genetic algorithm in laser scanning system
title_full_unstemmed Path optimization using genetic algorithm in laser scanning system
title_sort path optimization using genetic algorithm in laser scanning system
publishDate 2023
_version_ 1806424443931590656