A multi-criteria group-based decision-making method considering linguistic neutrosophic clouds

• Main Authors: Zhang, Lele, Zhang, Cheng, Tian, Guangdong, Chen, Zhaofang, Fathollahi-Fard, Amir M., Zhao, Xian-Gang, Wong, Kuan Yew
• Format: Article
• Published: Elsevier Ltd 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/107095/; http://dx.doi.org/10.1016/j.eswa.2023.119936
• Institution: Universiti Teknologi Malaysia

We can formulate complex automation systems with advanced decision-making methods. This work proposes a new multi-criteria group-based decision-making (MCGDM) method based on the linguistic neutrosophic cloud (LNC). As an efficient linguistic expression, the linguistic neutrosophic set (LNS) introduces linguistic terminology into a neutrosophic set to make it more complex. However, there are inherent problems with linguistic values and neutrosophic sets. First, existing operators cannot handle linguistic neutrosophic numbers (LNN) with extreme values while producing distorted results. Second, the subscript-based computation of linguistic values does not reflect the change of ambiguity during the operation. Third, the literature review rarely considers the randomness of uncertain variables. To eliminate the drawbacks of previous studies, this paper proposes a multi-criteria group-based decision-making (MCGDM) method considering the linguistic neutrosophic cloud (LNC). The proposed method presents a distance measure for LNCs based on Wasserstein distance and develops an improved MCGDM method based on weighted modified partial Hausdorff distance. With an extensive simulation, the feasibility of the proposed method is verified by solving an auto part selection problem. Finally, we show the superiority of the proposed method through a comparison with four different aggregation operators of LNNs in the literature review.