Multi-Criteria Supplier Evaluation/ Selection in Fuzzy Environment With Incomplete Decision Information

Incomplete information (or missing value) is a common problem in most of the real world business decisions. However, it can lead to seriously biased results. On the other side, some authors claim that supplier selection is a Multiple Attribute Decision Making/ Multiple Criteria Decision Making (MADM/ MCDM) problem, which is affected by several conflicting factors as the suppliers’ information and performances are usually incomplete and uncertain. Therefore, there is a need of models for handling incomplete and uncertain decision information. In order to reflect uncertainty of the given information, Fuzzy TOPSIS is applied. Whilst, in practice, Fuzzy TOPSIS technique is not applicable to incomplete information. Therefore, to resolve this limit, the Tamaddon et al. method (Tamaddon et al., 2009-the mathematical formulations for finding the missing data in the Data Envelopment Analysis [DEA; for crisp and interval data sets] environment), has been introduced in this paper. Further, in the proposed method, input and output factors play the role of cost and benefit respectively. In continuation, in this paper, a hybrid Fuzzy MADM/ MCDM (FMADM/ FMCDM) approach is proposed based on Tamaddon et al. method and Fuzzy TOPSIS approaches. In these hybrid models, the missing value is determined with Tamaddon et al. method after converting the fuzzy data sets to crisp and interval form, then Fuzzy TOPSIS model is used to obtain the final ranking of the suppliers in the supply chain context. In addition, comparative analysis has been performed, and the proposed model seems to be more satisfactory than the conventional method (ignoring and discarding incomplete decision information) in solving decision problems. The paper concludes with limitations and further research directions.