Cosine similarity and information measures of p,q,r- spherical fuzzy sets: Application in selecting migration destination

• Published in: Expert systems with applications 2025-03, Vol.265, Article 125932
• Main Authors: Rahim, Muhammad, Amin, Fazli, Alhabeeb, Somayah Abdualziz, Alshehri, Mansoor H., El-Wahed Khalifa, Hamiden Abd
• Format: Article
• Language: English
• Subjects: Decision making; Optimization; Similarity measures; Spherical fuzzy sets
• ISSN: 0957-4174
• DOI: 10.1016/j.eswa.2024.125932

The p,q,r- spherical fuzzy (p,q,r- SF) set represents a novel and flexible extension of picture fuzzy (PF), spherical fuzzy (SF), and T- spherical fuzzy (T- SF) sets, offering a key advantage through the introduction of three parameters p, q, and r. These parameters enable a precise adjustment of the influence of membership degrees, enhancing the flexibility of decision-making under uncertainty. The objective of this study is to introduce novel similarity measures for p,q,r- SF sets, including cosine, grey, and set-theoretic similarity measures. In addition, a multi-criteria decision-making (MCDM) approach is proposed, aimed at addressing real-life decision-making challenges. The significance of the proposed work lies in the ability to tailor the similarity measures according to the specific needs of decision-makers by manipulating the values of p, q, and r. To illustrate the effectiveness of the proposed methodology, a numerical example on migration destination selection is provided. The results highlight the impact of the parameters on the final decision outcomes, demonstrating the flexibility of the proposed approach. Additionally, a comparative analysis with existing methods confirms the advantages of the proposed similarity measures, emphasizing their enhanced adaptability and precision in decision-making tasks.