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Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics

The cost-based hybrid flow shop (CHFS) scheduling has been immensely studied due to its huge impact on productivity. For any profit-oriented organization, it is important to optimize total production costs. However, few researchers have studied hybrid flow shops (HFS) with total production cost util...

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Main Authors: Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim
Format: Article
Language:English
Published: SRN Intellectual Resources 2023
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/40059/1/Modeling%20and%20optimization%20of%20cost-based%20hybrid%20flow.pdf
http://umpir.ump.edu.my/id/eprint/40059/
https://doi.org/10.56225/ijgoia.v2i4.265
https://doi.org/10.56225/ijgoia.v2i4.265
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spelling my.ump.umpir.400592024-01-17T06:25:03Z http://umpir.ump.edu.my/id/eprint/40059/ Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics Ullah, Wasif Mohd Fadzil Faisae, Ab Rashid Muhammad Ammar, Nik Mu’tasim TJ Mechanical engineering and machinery The cost-based hybrid flow shop (CHFS) scheduling has been immensely studied due to its huge impact on productivity. For any profit-oriented organization, it is important to optimize total production costs. However, few researchers have studied hybrid flow shops (HFS) with total production cost utilization. This paper aims to develop a computational model and test the exploration capability of metaheuristics algorithms while optimizing the CHFS problem. Carlier and Neron defined three hypothetical benchmark problems for computational experiments. The popular optimization algorithms PSO, GA, and ACO were implemented on the CHFS model with ten optimization runs. The experimental results proven that ACO performed well regarding mean fitness value for all benchmark problems. Besides this, CPU time for PSO was very high compared to other algorithms. In the future, other optimization algorithms will be tested for the CHFS model, such as Teaching Learning Based Optimization (TLBO) and the Crayfish Optimization Algorithm (COA). SRN Intellectual Resources 2023-12 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/40059/1/Modeling%20and%20optimization%20of%20cost-based%20hybrid%20flow.pdf Ullah, Wasif and Mohd Fadzil Faisae, Ab Rashid and Muhammad Ammar, Nik Mu’tasim (2023) Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics. International Journal of Global Optimization and Its Application, 2 (4). pp. 244-254. ISSN 2948-4030. (Published) https://doi.org/10.56225/ijgoia.v2i4.265 https://doi.org/10.56225/ijgoia.v2i4.265
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
spellingShingle TJ Mechanical engineering and machinery
Ullah, Wasif
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
description The cost-based hybrid flow shop (CHFS) scheduling has been immensely studied due to its huge impact on productivity. For any profit-oriented organization, it is important to optimize total production costs. However, few researchers have studied hybrid flow shops (HFS) with total production cost utilization. This paper aims to develop a computational model and test the exploration capability of metaheuristics algorithms while optimizing the CHFS problem. Carlier and Neron defined three hypothetical benchmark problems for computational experiments. The popular optimization algorithms PSO, GA, and ACO were implemented on the CHFS model with ten optimization runs. The experimental results proven that ACO performed well regarding mean fitness value for all benchmark problems. Besides this, CPU time for PSO was very high compared to other algorithms. In the future, other optimization algorithms will be tested for the CHFS model, such as Teaching Learning Based Optimization (TLBO) and the Crayfish Optimization Algorithm (COA).
format Article
author Ullah, Wasif
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
author_facet Ullah, Wasif
Mohd Fadzil Faisae, Ab Rashid
Muhammad Ammar, Nik Mu’tasim
author_sort Ullah, Wasif
title Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
title_short Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
title_full Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
title_fullStr Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
title_full_unstemmed Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
title_sort modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
publisher SRN Intellectual Resources
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40059/1/Modeling%20and%20optimization%20of%20cost-based%20hybrid%20flow.pdf
http://umpir.ump.edu.my/id/eprint/40059/
https://doi.org/10.56225/ijgoia.v2i4.265
https://doi.org/10.56225/ijgoia.v2i4.265
_version_ 1822924089568788480
score 13.235362

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