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A whale optimization algorithm approach for flow shop scheduling to minimize makespan

Flow shop scheduling is crucial in manufacturing and production environments because it directly impacts output and overall production efficiency. It involves processing a set of jobs on multiple machines in a specific order. The objective is to determine the optimal job sequence that minimizes the...

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Main Authors: Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim
Format: Article
Language:English
Published: Penerbit UMP 2024
Subjects:
TJ Mechanical engineering and machinery
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/42706/1/43980.pdf
http://umpir.ump.edu.my/id/eprint/42706/
https://doi.org/10.15282/jmmst.v8i2.10762
https://doi.org/10.15282/jmmst.v8i2.10762
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spelling my.ump.umpir.427062024-10-02T07:38:38Z http://umpir.ump.edu.my/id/eprint/42706/ A whale optimization algorithm approach for flow shop scheduling to minimize makespan Mohd Abdul Hadi, Osman Mohd Fadzil Faisae, Ab Rashid Muhammad Ammar, Nik Mu’tasim TJ Mechanical engineering and machinery TS Manufactures Flow shop scheduling is crucial in manufacturing and production environments because it directly impacts output and overall production efficiency. It involves processing a set of jobs on multiple machines in a specific order. The objective is to determine the optimal job sequence that minimizes the makespan, which is the total time required to complete all jobs. This study proposes a computerized approach utilizing the Whale Optimization Algorithm (WOA) to solve the flow shop scheduling problem and minimize the makespan. The WOA is a recently developed meta-heuristic algorithm inspired by the bubble-net hunting strategy of humpback whales. The performance of the WOA is evaluated using five benchmark problems with varying numbers of jobs and machines, and the results are compared with those obtained from other algorithms reported in the literature, such as genetic algorithms and heuristic models. The findings demonstrate that the WOA can effectively solve the flow shop scheduling problem and provide improved makespan values, with an average efficiency of 7.33% compared to the other algorithms. Penerbit UMP 2024-09-29 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/42706/1/43980.pdf Mohd Abdul Hadi, Osman and Mohd Fadzil Faisae, Ab Rashid and Muhammad Ammar, Nik Mu’tasim (2024) A whale optimization algorithm approach for flow shop scheduling to minimize makespan. Journal of Modern Manufacturing Systems and Technology (JMMST), 8 (2). pp. 12-32. ISSN 2636-9575. (Published) https://doi.org/10.15282/jmmst.v8i2.10762 https://doi.org/10.15282/jmmst.v8i2.10762
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TJ Mechanical engineering and machinery
TS Manufactures
spellingShingle TJ Mechanical engineering and machinery
TS Manufactures
Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
A whale optimization algorithm approach for flow shop scheduling to minimize makespan
description Flow shop scheduling is crucial in manufacturing and production environments because it directly impacts output and overall production efficiency. It involves processing a set of jobs on multiple machines in a specific order. The objective is to determine the optimal job sequence that minimizes the makespan, which is the total time required to complete all jobs. This study proposes a computerized approach utilizing the Whale Optimization Algorithm (WOA) to solve the flow shop scheduling problem and minimize the makespan. The WOA is a recently developed meta-heuristic algorithm inspired by the bubble-net hunting strategy of humpback whales. The performance of the WOA is evaluated using five benchmark problems with varying numbers of jobs and machines, and the results are compared with those obtained from other algorithms reported in the literature, such as genetic algorithms and heuristic models. The findings demonstrate that the WOA can effectively solve the flow shop scheduling problem and provide improved makespan values, with an average efficiency of 7.33% compared to the other algorithms.
format Article
author Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
author_facet Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
author_sort Mohd Abdul Hadi, Osman
title A whale optimization algorithm approach for flow shop scheduling to minimize makespan
title_short A whale optimization algorithm approach for flow shop scheduling to minimize makespan
title_full A whale optimization algorithm approach for flow shop scheduling to minimize makespan
title_fullStr A whale optimization algorithm approach for flow shop scheduling to minimize makespan
title_full_unstemmed A whale optimization algorithm approach for flow shop scheduling to minimize makespan
title_sort whale optimization algorithm approach for flow shop scheduling to minimize makespan
publisher Penerbit UMP
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/42706/1/43980.pdf
http://umpir.ump.edu.my/id/eprint/42706/
https://doi.org/10.15282/jmmst.v8i2.10762
https://doi.org/10.15282/jmmst.v8i2.10762
_version_ 1822924699136425984
score 13.235362

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