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Article type: Research Article
Authors: Sultana, Ineena; * | Ahmed, Imtiazb | Azeem, Abdullahilb
Affiliations: [a] Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh | [b] Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
Correspondence: [*] Corresponding author. Ineen Sultana, Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Tejgaon Industrial Area, Dhaka-1208, Bangladesh. Tel.: +88 01671355743; E-mails: [email protected] (Ineen Sultana); [email protected] (Imtiaz Ahmed).
Abstract: In today’s competitive business, supplier selection problem plays a significant role as a strategic feature in company’s success. As variety of uncontrollable and unpredictable factors affect the evaluation and decision-making process at different levels, supplier selection problem is usually very complex and unstructured, Various decision making approaches have been proposed to tackle the problem as part of a general tendering process, particularly those of multi-criteria analysis which use both quantitative and qualitative data. The aim of this paper is to integrate Fuzzy Delphi method with fuzzy analytic hierarchy process (AHP) and Fuzzy TOPSIS based approach to select the best supplier providing the highest satisfaction for the criteria determined. Fuzzy Delphi method is used to identify the most important and significant criteria then Fuzzy AHP is used to obtain the relative importance of the evaluation criteria and finally Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to rank the suppliers with a view to select the best one from them. In order to demonstrate the applicability of proposed approach an illustrative example is presented and the result is analyzed at the end of this paper.
Keywords: Fuzzy Delphi method, Fuzzy AHP, Fuzzy TOPSIS, multi criteria supplier selection
DOI: 10.3233/IFS-141216
Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1273-1287, 2015
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