Green Supplier Selection Using Intuitionistic Fuzzy AHP and TOPSIS Methods: A Case Study from the Paper Mills

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Abstract

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of intuitionistic multi-criteria supplier selection methods in a fuzzy environment. The intuitionistic fuzzy AHP and TOPSIS methods are thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the paper mill. For this purpose, 3 alternative green suppliers have been identified. To evaluate the alternatives, 10 criteria in three dimensions including supplier performance, environmental protection and supplier risk have been selected. Since the Multi-Criteria Decision Making (MCDM) methods are often used in problem of supplier selection from past to present. The Intuitionistic Fuzzy Sets (IFS) are used to reflect approval, rejection, and hesitation of decision makers by dealing with real life uncertainty, imprecision, vagueness, and linguistic human decisions. The main purpose of this study is to define the weights of criteria with Intuitionistic Fuzzy AHP. After that, the Intuitionistic Fuzzy TOPSIS and AHP method were used to rank alternatives from best to worst. At the end of the study the results related with alternatives were compared and interpreted.

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APA

Demir, E., & Koca, G. (2021). Green Supplier Selection Using Intuitionistic Fuzzy AHP and TOPSIS Methods: A Case Study from the Paper Mills. In Advances in Intelligent Systems and Computing (Vol. 1197 AISC, pp. 666–673). Springer. https://doi.org/10.1007/978-3-030-51156-2_77

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