The Improved CURLI Method for Multi-Criteria Decision Making
Received: 5 December 2022 | Revised: 26 December 2022 | Accepted: 31 December 2022 | Online: 5 February 2023
Corresponding author: Anh-Tu Nguyen
Abstract
Multi-Criteria Decision Making (MCDM) investigates the best available choice in the presence of multiple conflicting criteria, whereas the Collaborative Unbiased Rank List Integration (CURLI) method has been proposed recently and has been applied in various fields of daily life. However, most previous works concentrated on analyzing cases in which the factor of a criterion is a specific quantity. The present paper proposes an approach developed from the original CURLI method, named Improved CURLI. This improvement helps solve a problem when the factors of the criteria can be linguistic variables or a data set. The proposed method is applied to rank the alternatives for two case studies: choosing the best grinding wheel and the best service suppliers. The ranking results are compared to those obtained using other methods. Furthermore, sensitivity analysis is also conducted to examine the stability and reliability of the ranking results in various scenarios. The results demonstrate the validity of the Improved CURLI method and prove that it is applicable for making decisions in various fields.
Keywords:
MCDM, CURLI method, improved CURLI method, data setDownloads
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