Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11413/6819
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Browsing Endüstri Mühendisliği Bölümü / Department of Industrial Engineering by Publisher "IOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS"
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Publication Metadata only A Combined Fuzzy AHP-goal Programming Approach to Assembly-Line Selection(IOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS, 2007) Ayağ, Zeki; Özdemir, Rifat Gürcan; TR141173; TR8785In mass production, assembly-line balancing (ALB) problem has been a critical and repetitive issue for companies for long time. On the other hand, equipment selection for stations has also been another important problem at the design stage of an assembly-line system. In this paper, both problems are handled simultaneously. Therefore first, goal programming (GP) method, a well-suited technique is used to develop a preemptive formulation to joint both of the problems, when the nature of the problem consists of several conflicting objectives, and some mathematical constraints on solutions. Second, an AHP method based on fuzzy scales which is incorporated with the GP is also used due to the fact that it takes both qualitative and quantitative judgments of decision-maker(s) into consideration to rank the equipment alternatives for stations by weight. The fuzzy AHP as one of the most commonly used multiple-criteria decision making (MCDM) methods has been effectively used for more than decade in both academic research and practice, and takes the vagueness and uncertainty on judgments of decision-maker(s) into consideration due to the fact that the crisp pairwise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). In short, in this study, a combined fuzzy AHP-GP approach is proposed to evaluating assembly-line design alternatives with equipment selection. An integer GP formulation is constructed, which also uses the fuzzy AHP scores of equipment alternatives, and employs them as one of the goals. Then, the mathematical model is solved to find out the ultimate alternative in terms of the minimized equipment cost and the maximized preference measures of decision-maker(s). The proposed approach is also illustrated on a sample case study.