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)
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Abstract
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.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Line balancing; Metaheuristic; MOTTA; Multiobjective optimization; Tiki-taka algorithm |
| Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Mechanical and Automotive Engineering Technology Institute of Postgraduate Studies |
| Depositing User: | Dr. Mohd Fadzil Faisae Ab. Rashid |
| Date Deposited: | 11 May 2023 07:23 |
| Last Modified: | 11 May 2023 07:23 |
| URI: | http://umpir.ump.edu.my/id/eprint/37577 |
| Download Statistic: | View Download Statistics |
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