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Path optimization using genetic algorithm evolution

Gantry robots are widely used in the industries for various material handling applications. The robot capable of moving in the Cartesian makes it very flexible and efficient at big or small areas. Path optimization to the robot would make it more efficient and easier automation. In this paper, genet...

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Main Authors: Low, C.Y., Chong, K.H., Salleh, K., Johnny, K.S.P.
Format: Conference Paper
Language:en_US
Published: 2017
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/7016
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spelling my.uniten.dspace-58282018-02-09T01:11:31Z Path optimization using genetic algorithm evolution Low, C.Y. Chong, K.H. Salleh, K. Johnny, K.S.P. Gantry robots are widely used in the industries for various material handling applications. The robot capable of moving in the Cartesian makes it very flexible and efficient at big or small areas. Path optimization to the robot would make it more efficient and easier automation. In this paper, genetic algorithm (GA) has been proposed to optimize the traveling sequence making the movement more efficient and economic as the total travel length is shortened. ©2010 IEEE. 2017-12-08T07:26:32Z 2017-12-08T07:26:32Z 2010 Conference Paper http://dspace.uniten.edu.my/jspui/handle/123456789/7016 10.1109/SCORED.2010.5704011 en_US Proceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010 2010, Article number 5704011, Pages 252-255
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/
language en_US
description Gantry robots are widely used in the industries for various material handling applications. The robot capable of moving in the Cartesian makes it very flexible and efficient at big or small areas. Path optimization to the robot would make it more efficient and easier automation. In this paper, genetic algorithm (GA) has been proposed to optimize the traveling sequence making the movement more efficient and economic as the total travel length is shortened. ©2010 IEEE.
format Conference Paper
author Low, C.Y.
Chong, K.H.
Salleh, K.
Johnny, K.S.P.
spellingShingle Low, C.Y.
Chong, K.H.
Salleh, K.
Johnny, K.S.P.
Path optimization using genetic algorithm evolution
author_facet Low, C.Y.
Chong, K.H.
Salleh, K.
Johnny, K.S.P.
author_sort Low, C.Y.
title Path optimization using genetic algorithm evolution
title_short Path optimization using genetic algorithm evolution
title_full Path optimization using genetic algorithm evolution
title_fullStr Path optimization using genetic algorithm evolution
title_full_unstemmed Path optimization using genetic algorithm evolution
title_sort path optimization using genetic algorithm evolution
publishDate 2017
url http://dspace.uniten.edu.my/jspui/handle/123456789/7016
_version_ 1644493786188873728
score 13.160551

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