Evaluation and Selection of Suppliers Using Intuitionistic Fuzzy DEA -TOPSIS Methods

Abstract

In the dynamic landscape of global supply chains, the effective evaluation and selection of suppliers play a pivotal role in ensuring organizational success and sustainability.  This study proposes a comprehensive approach that integrates Intuitionistic Fuzzy Data Envelopment Analysis (IF-DEA) with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to enhance the accuracy and robustness of supplier assessment.  The Intuitionistic Fuzzy DEA framework enables the consideration of uncertainties and vagueness inherent in supplier performance data, providing a more realistic representation of the evaluation process.  It considers not only the crisp data but also the hesitancy and ambiguity associated with subjective judgements.  Furthermore, the integration of TOPSIS allows for the determination of the optimal supplier from a set of alternatives by considering both ideal and nadir solutions. The proposed methodology is illustrated through a practical case study, wherein the performance of suppliers is assessed based on multiple criteria, including cost efficiency, delivery reliability, and product quality.  The results demonstrate the efficacy of the combined IF-DEA-TOPSIS approach in offering a systematic and comprehensive decision-making tool for supplier evaluation, considering both quantitative and qualitative aspects. This research contributes to the evolving field of supplier management by providing a novel and flexible methodology that addresses the challenges posed by uncertainty and subjectively in supplier assessment. The proposed approach not only aids organizations in making informed and strategic decisions but also contributes to the advancement of decision science in the context of supplier selection in supply chain management.