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Simulation of ant colony optimization on hole making performance

Hole making operation one of machining process widely used in industrial industry. One of the main criteria in determining the efficiency of machining performance in hole making operation is shortest machining time. In this paper, simulation approach based on Ant colony optimization (ACO) has b...

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Main Authors: Abdullah, Haslina, Tuan Zahari, Tuan Muhammad Lutfi, Zakaria, Mohamad Shukri
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
TS155-194 Production management. Operations management
Online Access:http://eprints.uthm.edu.my/2527/1/KP%202020%20%2861%29.pdf
http://eprints.uthm.edu.my/2527/
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spelling my.uthm.eprints.25272021-10-20T07:44:20Z http://eprints.uthm.edu.my/2527/ Simulation of ant colony optimization on hole making performance Abdullah, Haslina Tuan Zahari, Tuan Muhammad Lutfi Zakaria, Mohamad Shukri TS155-194 Production management. Operations management Hole making operation one of machining process widely used in industrial industry. One of the main criteria in determining the efficiency of machining performance in hole making operation is shortest machining time. In this paper, simulation approach based on Ant colony optimization (ACO) has been done on hole making operation in order to minimize the machining time. The result based on ACO has been compared with the result obtain based on Genetic Algorithm (GA). Based on the simulation results, the ACO is enhance the performance of hole making process by reducing 13.5% of machining time. The results show that ACO is capable to minimize the machining time of hole making procees. 2018-07 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/2527/1/KP%202020%20%2861%29.pdf Abdullah, Haslina and Tuan Zahari, Tuan Muhammad Lutfi and Zakaria, Mohamad Shukri (2018) Simulation of ant colony optimization on hole making performance. In: Innovative research and industrial dialogue 2018, 18 July 2018, UTEM.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TS155-194 Production management. Operations management
spellingShingle TS155-194 Production management. Operations management
Abdullah, Haslina
Tuan Zahari, Tuan Muhammad Lutfi
Zakaria, Mohamad Shukri
Simulation of ant colony optimization on hole making performance
description Hole making operation one of machining process widely used in industrial industry. One of the main criteria in determining the efficiency of machining performance in hole making operation is shortest machining time. In this paper, simulation approach based on Ant colony optimization (ACO) has been done on hole making operation in order to minimize the machining time. The result based on ACO has been compared with the result obtain based on Genetic Algorithm (GA). Based on the simulation results, the ACO is enhance the performance of hole making process by reducing 13.5% of machining time. The results show that ACO is capable to minimize the machining time of hole making procees.
format Conference or Workshop Item
author Abdullah, Haslina
Tuan Zahari, Tuan Muhammad Lutfi
Zakaria, Mohamad Shukri
author_facet Abdullah, Haslina
Tuan Zahari, Tuan Muhammad Lutfi
Zakaria, Mohamad Shukri
author_sort Abdullah, Haslina
title Simulation of ant colony optimization on hole making performance
title_short Simulation of ant colony optimization on hole making performance
title_full Simulation of ant colony optimization on hole making performance
title_fullStr Simulation of ant colony optimization on hole making performance
title_full_unstemmed Simulation of ant colony optimization on hole making performance
title_sort simulation of ant colony optimization on hole making performance
publishDate 2018
url http://eprints.uthm.edu.my/2527/1/KP%202020%20%2861%29.pdf
http://eprints.uthm.edu.my/2527/
_version_ 1738581002447486976
score 13.211869

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