Business environment is characterized by greater domestic and international competitive position in the global market. Vendors play a key role in achieving the so-called corporate competition. It is not easy however to identify good vendors because evaluation is based on multiple criteria. In practice, for VSP most of the input information about the criteria is not known precisely. Intuitionistic fuzzy set is an extension of the classical fuzzy set theory (FST), which is a suitable way to deal with impreciseness. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom called nonmembership function into the set description. In this paper, we proposed a triangular intuitionistic fuzzy number based approach for the vendor selection problem using analytical hierarchy process. The crisp data of the vendors is represented in the form of triangular intuitionistic fuzzy numbers. By applying AHP which involves decomposition, pairwise comparison, and deriving priorities for the various levels of the hierarchy, an overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our method. Lastly a sensitivity analysis is performed to find the most critical criterion on the basis of which vendor is selected.

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Modern businesses face a more severe and challenging environment than before. Selection of vendor and evaluating its performance are decisions of strategic importance from business point of view. Selecting vendors involve those that perform optimally on the desired multicriteria dimensions like cost, quality, delivery performance, etc. In this paper we identify the major criteria for selecting vendors and develop a hierarchy through which decision maker can examine the relationship among these criteria. Some of these criteria possess characteristics of fuzziness. By applying analytical hierarchy process (AHP) based on fuzzy preference programming (FPP) a pair wise comparison is made between criteria. The whole process of fuzzy AHP involves decomposition, pairwise comparison, interval comparison, derive priorities using optimization technique of FPP. An overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our methodology.

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