A new multiobjective tiki-taka algorithm for optimization of assembly line balancing
Purpose: This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simu...
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| Format: | Article |
| Language: | English English |
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Emerald Group Publishing Ltd.
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/37577/ http://umpir.ump.edu.my/id/eprint/37577/1/2023%20MOTTA%20Eng%20Comp.pdf http://umpir.ump.edu.my/id/eprint/37577/7/A%20new%20multiobjective%20tiki-taka%20algorithm%20for%20optimization%20of%20assembly%20line%20balancing.pdf |
| _version_ | 1848825288195047424 |
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| author | M. F. F., Ab Rashid Ariff Nijay, Ramli |
| author_facet | M. F. F., Ab Rashid Ariff Nijay, Ramli |
| author_sort | M. F. F., Ab Rashid |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Purpose: This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simultaneously. Design/methodology/approach: TTA is a new metaheuristic inspired by the tiki-taka playing style in a football match. The TTA is previously designed for a single-objective optimization, but this study extends TTA into a multiobjective optimization. The MOTTA mimics the short passing and player movement in tiki-taka to control the game. The algorithm also utilizes unsuccessful ball pass and multiple key players to enhance the exploration. MOTTA was tested against popular CEC09 benchmark functions. Findings: The computational experiments indicated that MOTTA had better results in 82% of the cases from the CEC09 benchmark functions. In addition, MOTTA successfully found 83.3% of the Pareto optimal solution in the SALB-E optimization and showed tremendous performance in the spread and distribution indicators, which were associated with the multiple key players in the algorithm. Originality/value: MOTTA exploits the information from all players to move to a new position. The algorithm makes all solution candidates have contributions to the algorithm convergence. |
| first_indexed | 2025-11-15T03:26:32Z |
| format | Article |
| id | ump-37577 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T03:26:32Z |
| publishDate | 2023 |
| publisher | Emerald Group Publishing Ltd. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-375772023-05-11T07:23:37Z http://umpir.ump.edu.my/id/eprint/37577/ A new multiobjective tiki-taka algorithm for optimization of assembly line balancing M. F. F., Ab Rashid Ariff Nijay, Ramli TJ Mechanical engineering and machinery TS Manufactures Purpose: This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simultaneously. Design/methodology/approach: TTA is a new metaheuristic inspired by the tiki-taka playing style in a football match. The TTA is previously designed for a single-objective optimization, but this study extends TTA into a multiobjective optimization. The MOTTA mimics the short passing and player movement in tiki-taka to control the game. The algorithm also utilizes unsuccessful ball pass and multiple key players to enhance the exploration. MOTTA was tested against popular CEC09 benchmark functions. Findings: The computational experiments indicated that MOTTA had better results in 82% of the cases from the CEC09 benchmark functions. In addition, MOTTA successfully found 83.3% of the Pareto optimal solution in the SALB-E optimization and showed tremendous performance in the spread and distribution indicators, which were associated with the multiple key players in the algorithm. Originality/value: MOTTA exploits the information from all players to move to a new position. The algorithm makes all solution candidates have contributions to the algorithm convergence. Emerald Group Publishing Ltd. 2023 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/37577/1/2023%20MOTTA%20Eng%20Comp.pdf pdf en http://umpir.ump.edu.my/id/eprint/37577/7/A%20new%20multiobjective%20tiki-taka%20algorithm%20for%20optimization%20of%20assembly%20line%20balancing.pdf M. F. F., Ab Rashid and Ariff Nijay, Ramli (2023) A new multiobjective tiki-taka algorithm for optimization of assembly line balancing. Engineering Computations. pp. 1-30. ISSN 0264-4401. (In Press / Online First) (In Press / Online First) https://doi.org/10.1108/EC-03-2022-0185 https://doi.org/10.1108/EC-03-2022-0185 |
| spellingShingle | TJ Mechanical engineering and machinery TS Manufactures M. F. F., Ab Rashid Ariff Nijay, Ramli A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title | A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title_full | A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title_fullStr | A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title_full_unstemmed | A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title_short | A new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| title_sort | new multiobjective tiki-taka algorithm for optimization of assembly line balancing |
| topic | TJ Mechanical engineering and machinery TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/37577/ http://umpir.ump.edu.my/id/eprint/37577/ http://umpir.ump.edu.my/id/eprint/37577/ http://umpir.ump.edu.my/id/eprint/37577/1/2023%20MOTTA%20Eng%20Comp.pdf http://umpir.ump.edu.my/id/eprint/37577/7/A%20new%20multiobjective%20tiki-taka%20algorithm%20for%20optimization%20of%20assembly%20line%20balancing.pdf |