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Recent trend in mixed-model assembly line balancing optimization using soft computing approaches

Razali, Muhamad Magffierah and Kamarudin, N.H. and M. F. F., Ab Rashid and Ahmad Nasser, Mohd Rose (2019) Recent trend in mixed-model assembly line balancing optimization using soft computing approaches. Engineering Computations, 36 (2). pp. 622-645. ISSN 0264-4401

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Purpose - This paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic polynomial-time hard problem which requires an effective algorithm for solution. This problem has attracted a number of research fields: manufacturing, mathematics and computer science. Design/methodology/approach - This paper review 59 published research works on MMALB from indexed journal. The review includes MMALB problem varieties, optimization algorithm, objective function and constraints in the problem. Findings - Based on research trend, this topic is still growing with the highest publication number observed in 2016 and 2017. The review indicated that the future research direction should focus on human factors and sustainable issues in the problem modeling. As the assembly cost becomes crucial, resource utilization in the assembly line should also be considered. Apart from that, the growth of new optimization algorithms is predicted to influence the MMALB optimization, which currently relies on well-established algorithms. Originality/value - The originality of this paper is on the research trend in MMALB. It provides the future direction for the researchers in this field.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Assembly; Assembly machines; Manufacture; Optimization; Polynomial approximation; Soft computing
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TS Manufactures
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Dr. Mohd Fadzil Faisae Ab. Rashid
Date Deposited: 21 Nov 2019 02:28
Last Modified: 21 Nov 2019 02:28
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