Supplier Selection Incorporating Weights of Criteria using an Order Preference by Similarity Method and Interval-valued Intuitionistic Fuzzy Sets

• Published in: 8th International Conference on Recent Advances and Innovations in Engineering: Empowering Computing, Analytics, and Engineering Through Digital Innovation, ICRAIE 2023
• Main Author: Abdullah L.; Najib N.M.; Azzah Awang N.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189938144&doi=10.1109%2fICRAIE59459.2023.10468119&partnerID=40&md5=33aea6872938b55f25923852c519c24e

Choosing an appropriate supplier involving multiple choices is a complex decision to maximize the overall profit and increase customer satisfaction. This paper proposed the TOPSIS-based method and interval-valued intuitionistic fuzzy sets (IVIFS) to deal with multiplicity in solving food supplier selection. In this study, the qualitative evaluations concerning criteria are described by IVIFS linguistic variables. The linguistic evaluations are analyzed using the ten-step computational procedures including entropy weight of criteria and relative weight. The closeness coefficient and score degree of alternatives is obtained to select the best performer. The findings suggest that the supplier Hex-food (A3) was the most preferred as this alternative scored the highest closeness coefficient and score function and C3 (delivery performance) was the most important criterion. This study contributes to assisting the practicality of business in selecting the best supplier and provides some insights to the potential food manufacturers in choosing the appropriate supplier. © 2023 IEEE.