Cover Image

Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm

Hybrid flow shop scheduling (HFS) involves optimizing production processes, where different manufacturing stages have varying capacities, combining parallel machine and flow shop scheduling to improve efficiency and reduce production time. Incorporating energy considerations into HFS problems has em...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim
Format: Article
Language:English
Published: Faculty Mechanical Engineering, UMP 2024
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/42705/1/10796-Article%20Text-38611-44010-10-20240930.pdf
http://umpir.ump.edu.my/id/eprint/42705/
https://doi.org/10.15282/jmes.18.3.2024.6.0803
https://doi.org/10.15282/jmes.18.3.2024.6.0803
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.42705
record_format eprints
spelling my.ump.umpir.427052024-10-02T07:34:37Z http://umpir.ump.edu.my/id/eprint/42705/ Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm Mohd Abdul Hadi, Osman Mohd Fadzil Faisae, Ab Rashid Nik Mohd Zuki, Nik Mohamed Muhammad Ammar, Nik Mu’tasim TS Manufactures Hybrid flow shop scheduling (HFS) involves optimizing production processes, where different manufacturing stages have varying capacities, combining parallel machine and flow shop scheduling to improve efficiency and reduce production time. Incorporating energy considerations into HFS problems has emerged as a critical area of research, driven by the growing emphasis on environmental sustainability and cost-effectiveness in manufacturing operations. This study addresses the hybrid flow shop scheduling with energy consideration (HFSE) problem, aiming to simultaneously optimize makespan and total energy consumption, two conflicting objectives. An Artificial Bee Colony (ABC) algorithm is proposed as an effective solution methodology for tackling the HFSE problem. Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. The proposed approach's ability to efficiently explore the search space and balance the trade-offs between makespan minimization and energy consumption reduction contributed to its superior results. The ABC algorithm reduces makespan and energy consumption by 2.95% and 3.43%, respectively. This finding suggests potential benefits for manufacturing operations, including decreased production time and lower operational costs. Faculty Mechanical Engineering, UMP 2024-09-30 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/42705/1/10796-Article%20Text-38611-44010-10-20240930.pdf Mohd Abdul Hadi, Osman and Mohd Fadzil Faisae, Ab Rashid and Nik Mohd Zuki, Nik Mohamed and Muhammad Ammar, Nik Mu’tasim (2024) Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm. Journal of Mechanical Engineering and Sciences (JMES), 18 (3). 10171 -10180. ISSN 2289-4659 (print); 2231-8380 (online). (Published) https://doi.org/10.15282/jmes.18.3.2024.6.0803 https://doi.org/10.15282/jmes.18.3.2024.6.0803
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 TS Manufactures
spellingShingle TS Manufactures
Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Nik Mohd Zuki, Nik Mohamed
Muhammad Ammar, Nik Mu’tasim
Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
description Hybrid flow shop scheduling (HFS) involves optimizing production processes, where different manufacturing stages have varying capacities, combining parallel machine and flow shop scheduling to improve efficiency and reduce production time. Incorporating energy considerations into HFS problems has emerged as a critical area of research, driven by the growing emphasis on environmental sustainability and cost-effectiveness in manufacturing operations. This study addresses the hybrid flow shop scheduling with energy consideration (HFSE) problem, aiming to simultaneously optimize makespan and total energy consumption, two conflicting objectives. An Artificial Bee Colony (ABC) algorithm is proposed as an effective solution methodology for tackling the HFSE problem. Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. The proposed approach's ability to efficiently explore the search space and balance the trade-offs between makespan minimization and energy consumption reduction contributed to its superior results. The ABC algorithm reduces makespan and energy consumption by 2.95% and 3.43%, respectively. This finding suggests potential benefits for manufacturing operations, including decreased production time and lower operational costs.
format Article
author Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Nik Mohd Zuki, Nik Mohamed
Muhammad Ammar, Nik Mu’tasim
author_facet Mohd Abdul Hadi, Osman
Mohd Fadzil Faisae, Ab Rashid
Nik Mohd Zuki, Nik Mohamed
Muhammad Ammar, Nik Mu’tasim
author_sort Mohd Abdul Hadi, Osman
title Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
title_short Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
title_full Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
title_fullStr Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
title_full_unstemmed Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
title_sort energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
publisher Faculty Mechanical Engineering, UMP
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/42705/1/10796-Article%20Text-38611-44010-10-20240930.pdf
http://umpir.ump.edu.my/id/eprint/42705/
https://doi.org/10.15282/jmes.18.3.2024.6.0803
https://doi.org/10.15282/jmes.18.3.2024.6.0803
_version_ 1822924698977042432
score 13.235362

Similar Items