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Multiobjective Fuzzy Mixed Assembly Line Sequencing Optimization Model

Tahriri, Farzad and Siti Zawiah, Md Dawal and Zahari, Taha (2014) Multiobjective Fuzzy Mixed Assembly Line Sequencing Optimization Model. Journal of Applied Mathematics. pp. 1-19. ISSN 1110-757X (print); 1687-0042 (online)

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It can be deduced from previous studies that there exists a research gap in assembly line sequencing optimization model for mixed-model production lines. In particular, there is a lack of studies which focus on the integration between job shop and assembly lines using fuzzy techniques. Hence, this paper is aimed at addressing the multiobjective mixed-model assembly line sequencing problem by integrating job shop and assembly production lines for factories with modular layouts. The primary goal is to minimize the make-span, setup time, and cost simultaneously in mixed-model assembly lines. Such conflicting goals arise when switching between different products. A genetic algorithm (GA) approach is used to solve this problem, in which trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data.

Item Type: Article
Additional Information: Indexed in Scopus. Article ID: 179085
Uncontrolled Keywords: Fuzzy techniques
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 28 Apr 2015 08:26
Last Modified: 22 Jan 2018 02:54
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