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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization

Hybrid flow shop with energy consumption (HFS-EC) combine the flow shop scheduling and parallel machine scheduling problem with the aim to optimize energy utilization, besides regular makespan in the production scheduling. This paper optimizes an HFS-EC case study using Moth Flame Optimization (MFO)...

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Main Authors: M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.
Format: Conference or Workshop Item
Language:English
English
Published: Springer 2022
Subjects:
TJ Mechanical engineering and machinery
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/37575/1/2022%20i3mf%20HFS%20EE%20MFO.pdf
http://umpir.ump.edu.my/id/eprint/37575/7/Hybrid%20flow%20shop%20scheduling%20with%20energy%20consumption%20in%20machine%20shop%20.pdf
http://umpir.ump.edu.my/id/eprint/37575/
https://doi.org/10.1007/978-981-33-4597-3_8
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spelling my.ump.umpir.375752023-05-12T02:07:48Z http://umpir.ump.edu.my/id/eprint/37575/ Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization M. F. F., Ab Rashid Ahmad Nasser, Mohd Rose N. M. Zuki, N. M. TJ Mechanical engineering and machinery TS Manufactures Hybrid flow shop with energy consumption (HFS-EC) combine the flow shop scheduling and parallel machine scheduling problem with the aim to optimize energy utilization, besides regular makespan in the production scheduling. This paper optimizes an HFS-EC case study using Moth Flame Optimization (MFO). The case study has been conducted in a machine shop concentrating on three machining types; lathe, milling and deburring. The objectives were to optimize makespan and total energy consumption in the machine schedule. Optimization using MFO has been conducted and the results was compared with well-established algorithm like Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization. The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. Although there were other solutions with better individual optimization objectives, but results obtained by MFO compromised between minimum makespan and energy consumption. The proposed HFS-EC model and MFO algorithm has a great potential to be implemented in other scheduling case study due to benefit of reducing carbon emission and at the same time maintain the production output. Springer 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/37575/1/2022%20i3mf%20HFS%20EE%20MFO.pdf pdf en http://umpir.ump.edu.my/id/eprint/37575/7/Hybrid%20flow%20shop%20scheduling%20with%20energy%20consumption%20in%20machine%20shop%20.pdf M. F. F., Ab Rashid and Ahmad Nasser, Mohd Rose and N. M. Zuki, N. M. (2022) Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization. In: Lecture Notes in Electrical Engineering; Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2020, 6 August 2020 , Gambang, Kuantan. pp. 77-86., 730 (262829). ISSN 1876-1100 ISBN 978-981334596-6 https://doi.org/10.1007/978-981-33-4597-3_8
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TJ Mechanical engineering and machinery
TS Manufactures
spellingShingle TJ Mechanical engineering and machinery
TS Manufactures
M. F. F., Ab Rashid
Ahmad Nasser, Mohd Rose
N. M. Zuki, N. M.
Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
description Hybrid flow shop with energy consumption (HFS-EC) combine the flow shop scheduling and parallel machine scheduling problem with the aim to optimize energy utilization, besides regular makespan in the production scheduling. This paper optimizes an HFS-EC case study using Moth Flame Optimization (MFO). The case study has been conducted in a machine shop concentrating on three machining types; lathe, milling and deburring. The objectives were to optimize makespan and total energy consumption in the machine schedule. Optimization using MFO has been conducted and the results was compared with well-established algorithm like Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization. The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. Although there were other solutions with better individual optimization objectives, but results obtained by MFO compromised between minimum makespan and energy consumption. The proposed HFS-EC model and MFO algorithm has a great potential to be implemented in other scheduling case study due to benefit of reducing carbon emission and at the same time maintain the production output.
format Conference or Workshop Item
author M. F. F., Ab Rashid
Ahmad Nasser, Mohd Rose
N. M. Zuki, N. M.
author_facet M. F. F., Ab Rashid
Ahmad Nasser, Mohd Rose
N. M. Zuki, N. M.
author_sort M. F. F., Ab Rashid
title Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
title_short Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
title_full Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
title_fullStr Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
title_full_unstemmed Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
title_sort hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization
publisher Springer
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/37575/1/2022%20i3mf%20HFS%20EE%20MFO.pdf
http://umpir.ump.edu.my/id/eprint/37575/7/Hybrid%20flow%20shop%20scheduling%20with%20energy%20consumption%20in%20machine%20shop%20.pdf
http://umpir.ump.edu.my/id/eprint/37575/
https://doi.org/10.1007/978-981-33-4597-3_8
_version_ 1768006871505960960
score 13.222552

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