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Minimize the makespan for job shop scheduling problem using artificial immune system approach

In the manufacturing industry, scheduling is a process of arranging, controlling and optimizing work and workloads in a production process. This research discussed about job-shop scheduling problem. The main problem in job-shop scheduling is to optimize the usage of machines in order to obtain the s...

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Main Authors:	Muhamad, A. S., Deris, S., Zakaria, Z.
Format:	Article
Published:	Asian Research Publishing Network 2015
Subjects:	T58.5-58.64 Information technology
Online Access:	http://eprints.utm.my/id/eprint/58562/
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id	my.utm.58562
record_format	eprints
spelling	my.utm.585622021-10-28T07:32:37Z http://eprints.utm.my/id/eprint/58562/ Minimize the makespan for job shop scheduling problem using artificial immune system approach Muhamad, A. S. Deris, S. Zakaria, Z. T58.5-58.64 Information technology In the manufacturing industry, scheduling is a process of arranging, controlling and optimizing work and workloads in a production process. This research discussed about job-shop scheduling problem. The main problem in job-shop scheduling is to optimize the usage of machines in order to obtain the shortest time in completing the activities. Several methods have been used to solve job-shop scheduling problems and the method proposed here is artificial intelligence by using the artificial immune system algorithm (AIS). The advantage of this algorithm is fabricated by imitating the natural immune system. The results produced by this method are compared with the best results of the previous research. Asian Research Publishing Network 2015 Article PeerReviewed Muhamad, A. S. and Deris, S. and Zakaria, Z. (2015) Minimize the makespan for job shop scheduling problem using artificial immune system approach. Journal Of Theoretical And Applied Information Technology, 80 (1). pp. 141-146. ISSN 1992-8645
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	T58.5-58.64 Information technology
spellingShingle	T58.5-58.64 Information technology Muhamad, A. S. Deris, S. Zakaria, Z. Minimize the makespan for job shop scheduling problem using artificial immune system approach
description	In the manufacturing industry, scheduling is a process of arranging, controlling and optimizing work and workloads in a production process. This research discussed about job-shop scheduling problem. The main problem in job-shop scheduling is to optimize the usage of machines in order to obtain the shortest time in completing the activities. Several methods have been used to solve job-shop scheduling problems and the method proposed here is artificial intelligence by using the artificial immune system algorithm (AIS). The advantage of this algorithm is fabricated by imitating the natural immune system. The results produced by this method are compared with the best results of the previous research.
format	Article
author	Muhamad, A. S. Deris, S. Zakaria, Z.
author_facet	Muhamad, A. S. Deris, S. Zakaria, Z.
author_sort	Muhamad, A. S.
title	Minimize the makespan for job shop scheduling problem using artificial immune system approach
title_short	Minimize the makespan for job shop scheduling problem using artificial immune system approach
title_full	Minimize the makespan for job shop scheduling problem using artificial immune system approach
title_fullStr	Minimize the makespan for job shop scheduling problem using artificial immune system approach
title_full_unstemmed	Minimize the makespan for job shop scheduling problem using artificial immune system approach
title_sort	minimize the makespan for job shop scheduling problem using artificial immune system approach
publisher	Asian Research Publishing Network
publishDate	2015
url	http://eprints.utm.my/id/eprint/58562/
_version_	1715189644199460864
score	13.18916

Minimize the makespan for job shop scheduling problem using artificial immune system approach

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