Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17975
Title: Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOPSIS
Authors: Samvedi, A
Jain, V
Chan, FTS 
Issue Date: 2013
Source: International journal of production research, 2013, v. 51, no. 8, p. 2433-2442
Abstract: Risk is inherent in almost every activity of supply chain management. With the ever-increasing push for efficiency, supply chains today are getting more and more risky. Adding to the difficulty of dealing with these risks is the amount of subjectivity and uncertainty involved. This makes analytical examination of the situation very difficult, especially as the amount of information available at a particular time is not sufficient for such an analysis. Thus a supply chain risk index, which captures the level of risk faced by a supply chain in a given situation, is the need of the hour. This study is an effort towards quantifying the risks in a supply chain and then consolidating the values into a comprehensive risk index. An integrated approach, with a fuzzy analytical hierarchy process (AHP) and a fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) as its important elements, has been used for this purpose. Fuzzy values in this study help in capturing the subjectivity of the situation with a final conversion to a crisp value which is much more comprehensible. A case study is used to illustrate the proposed methodology.
Keywords: fuzzy AHP
fuzzy TOPSIS
risk index
supply chain risk management
Publisher: Taylor & Francis
Journal: International journal of production research 
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207543.2012.741330
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