Abstract
Selecting optimal suppliers in fuzzy environments has become a major challenge for enterprises. Reputation plays an important role in the process of supplier selection because of its fuzziness, dynamicity, and transitivity. In this study, we first present a novel intuitionistic fuzzy sets (IFS)-hyperlink-induced topic search (HITS) method that combines the intuitionistic fuzzy set with the hyperlink-induced topic search (HITS) algorithm to extend the ability of processing fuzzy information in order to obtain post-propagated reputation values of suppliers. Then, we employ the dynamic intuitionistic fuzzy weighted average operator to gain dynamic reputation values and other evaluation attribute values. After that, intuitionistic fuzzy entropy weight method is adopted to acquire more accurate weights for each evaluation attribute. Finally, we employ the Vlsekriterijumska Optimizacija I Kompromisno Resenje method to acquire comprehensive evaluation values of candidate supplier to select optimal suppliers. Two groups of experiments for supplier selection are given to explain feasibility and practicality of the proposed method.
Highlights
With the rapid development of information technologies, an increasing number of enterprises have developed and deployed electronic procurement systems to improve the efficiency and quality of procurement [1,2]
Boran et al [7] incorporated the technique for order preference by similarity to ideal solution method into intuitionistic fuzzy sets (IFSs) to select an appropriate supplier
Considering the drawbacks of the traditional hyperlink-induced topic search (HITS) algorithm, we propose a new method (i.e., IFS-HITS), which combines IFSs with the HITS algorithm to obtain post-propagated reputation values
Summary
With the rapid development of information technologies, an increasing number of enterprises have developed and deployed electronic procurement systems to improve the efficiency and quality of procurement [1,2]. Narasimhan et al [6] constructed a multi-product, multi-criteria model product to optimize supplier selection with life-cycle considerations. In our previous work [9], we combined the extended fuzzy AHP with fuzzy grey relational analysis to obtain optimal suppliers. To address the aforementioned issues, we first present a novel IFS-HITS approach that combines IFSs with the hyperlink-induced topic search (HITS) algorithm to obtain post-propagated reputation values of suppliers in the fuzzy environment. We conclude with our main contributions and present suggestions for future research
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