Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP)
The flowshop is the most often used production system in the sector, and several efforts have been made to improve its efficiency. The NEH (Nawaz, Enscore and Ham) heuristics are one of the promising techniques. The range includes using heuristics and metaheuristics. By adopting a modified version...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
semarak ilmu
2024
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/11724/1/J17049_dc42116b1c7b13d2240ed565f60c65bb.pdf |
| _version_ | 1817857243490549760 |
|---|---|
| author | Sidek, Noor Azizah Bareduan, Salleh Ahmad Nawawi, Azli Jia Yee, Ten |
| author_facet | Sidek, Noor Azizah Bareduan, Salleh Ahmad Nawawi, Azli Jia Yee, Ten |
| author_sort | Sidek, Noor Azizah |
| collection | UTHM |
| description | The flowshop is the most often used production system in the sector, and several efforts have been made to improve its efficiency. The NEH (Nawaz, Enscore and Ham) heuristics
are one of the promising techniques. The range includes using heuristics and metaheuristics. By adopting a modified version of the Artificial Bee Colony (ABC) algorithm, which has the disadvantage of a slow converge speed, this study aims to boost NEH. To find high-quality results with a faster convergence rate, this study developed a strategy to increase the convergence speed of ABC. Because of the significant performance in the makespan value (performance indicator), the Total Greedy was adopted in this study, and the author continued to use it throughout the remainder of the research. This study suggested creating a Guided Artificial Bee Colony
(GABC) using the First Job Sequence Arrangement Method and the NEH idea. The investigation was based on Taillard benchmark datasets. According to the findings, ABC
frequently gave inconsistent outcomes, but surprisingly, GABC, NEH-based ABC, and ABC consistently produced results that were each 68.75%, 63.33%, and 0.01% better
than NEH. Finally, the author can state that this analysis validated ABC's slow convergence problem solutions. |
| first_indexed | 2024-12-08T07:42:43Z |
| format | Article |
| id | uthm.eprints-11724 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-12-08T07:42:43Z |
| publishDate | 2024 |
| publisher | semarak ilmu |
| record_format | dspace |
| spelling | uthm.eprints-117242024-11-27T07:20:40Z http://eprints.uthm.edu.my/11724/ Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) Sidek, Noor Azizah Bareduan, Salleh Ahmad Nawawi, Azli Jia Yee, Ten T55.4-60.8 Industrial engineering. Management engineering The flowshop is the most often used production system in the sector, and several efforts have been made to improve its efficiency. The NEH (Nawaz, Enscore and Ham) heuristics are one of the promising techniques. The range includes using heuristics and metaheuristics. By adopting a modified version of the Artificial Bee Colony (ABC) algorithm, which has the disadvantage of a slow converge speed, this study aims to boost NEH. To find high-quality results with a faster convergence rate, this study developed a strategy to increase the convergence speed of ABC. Because of the significant performance in the makespan value (performance indicator), the Total Greedy was adopted in this study, and the author continued to use it throughout the remainder of the research. This study suggested creating a Guided Artificial Bee Colony (GABC) using the First Job Sequence Arrangement Method and the NEH idea. The investigation was based on Taillard benchmark datasets. According to the findings, ABC frequently gave inconsistent outcomes, but surprisingly, GABC, NEH-based ABC, and ABC consistently produced results that were each 68.75%, 63.33%, and 0.01% better than NEH. Finally, the author can state that this analysis validated ABC's slow convergence problem solutions. semarak ilmu 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/11724/1/J17049_dc42116b1c7b13d2240ed565f60c65bb.pdf Sidek, Noor Azizah and Bareduan, Salleh Ahmad and Nawawi, Azli and Jia Yee, Ten (2024) Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP). Journal of Advanced Research in Applied Sciences and Engineering Technology, 33 (3). pp. 393-406. ISSN 2462-1943 https://doi.org/10.37934/araset.33.3.393406 |
| spellingShingle | T55.4-60.8 Industrial engineering. Management engineering Sidek, Noor Azizah Bareduan, Salleh Ahmad Nawawi, Azli Jia Yee, Ten Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title | Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title_full | Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title_fullStr | Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title_full_unstemmed | Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title_short | Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) |
| title_sort | development of guided artificial bee colony gabc heuristic for permutation flowshop scheduling problem pfsp |
| topic | T55.4-60.8 Industrial engineering. Management engineering |
| url | http://eprints.uthm.edu.my/11724/1/J17049_dc42116b1c7b13d2240ed565f60c65bb.pdf |
| work_keys_str_mv | AT sideknoorazizah developmentofguidedartificialbeecolonygabcheuristicforpermutationflowshopschedulingproblempfsp AT bareduansallehahmad developmentofguidedartificialbeecolonygabcheuristicforpermutationflowshopschedulingproblempfsp AT nawawiazli developmentofguidedartificialbeecolonygabcheuristicforpermutationflowshopschedulingproblempfsp AT jiayeeten developmentofguidedartificialbeecolonygabcheuristicforpermutationflowshopschedulingproblempfsp |