A new multiobjective tiki-taka algorithm for optimization of assembly line balancing
ISSN: 0264-4401
Article publication date: 20 April 2023
Issue publication date: 2 June 2023
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.
Keywords
Acknowledgements
The authors would like to acknowledge the Universiti Malaysia Pahang for funding this research under UMP Distinguished Research Grant (RDU223017).
Citation
Ab. Rashid, M.F.F. and Ramli, A.N. (2023), "A new multiobjective tiki-taka algorithm for optimization of assembly line balancing", Engineering Computations, Vol. 40 No. 3, pp. 564-593. https://doi.org/10.1108/EC-03-2022-0185
Publisher
:Emerald Publishing Limited
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