Fuzzy Topsis with Ratings Based on Sub-Criteria for Selection of Supplier

• Published in: 2024 5th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2024 - Proceedings
• Main Author: Razak S.A.; Ramli N.; Azmi M.I.H.N.; Nor M.I.M.; Noreddie H.A.H.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209626567&doi=10.1109%2fAiDAS63860.2024.10730581&partnerID=40&md5=7ab0fd89a66cc6d9b57481b4b5438e7e

The success of a company greatly depends on the supplier's selection. Similar to traditional approaches, the process of supplier selection relies on human assessment, which is inherently subjective and vague. The fuzzy TOPSIS has been successfully applied in many multi-criteria decision-making processes in uncertain environments, including the selection of suppliers. The majority of fuzzy TOPSIS methods take into account the ratings of alternatives for each primary criterion. However, there is still a shortage of studies that utilise ratings based on sub-criteria. This paper aims to determine the optimal criteria for selecting a supplier in the Information Technology (IT) business, with the ratings assigned according to sub-criteria related to benefits and costs. Furthermore, the study aims to determine the finest supplier meeting the established criteria within the IT industry. There are two phases involved, where the first phase consists of converting the benefit and cost sub-criteria into the main criteria using the normalisation and averaging method, and the second phase involves the Closeness Coefficient (CC), Fuzzy Positive Ideal Solution (FPIS), Fuzzy Negative Ideal Solution (FNIS) and the ranking using the centroid method. The outcomes indicated that among the four accessible suppliers, Supplier 1 (S1) is the best option, followed by Supplier 2 (S2), Supplier 4 (S4) and Supplier 3 (S3). The study also determines the criteria that need to be prioritised, which are product performance and service performance. Fuzzy TOPSIS, which has ratings based on benefit and cost sub-criteria, has the potential to automate the procedure and address vagueness or uncertainty during the selection process. © 2024 IEEE.