Complex fuzzy rough aggregation operators and their applications in EDAS for multi-criteria group decision-making

Abstract

One of the notable advantages of the complex fuzzy set is its ability to incorporate not only satisfaction and dissatisfaction but also the absence of vague information in two-dimensional scenarios. By combining a fuzzy rough set with a complex fuzzy set, this study aims to provide a powerful and versatile tool for multi-criteria group decision-making (MCGDM) in complex and uncertain situations. This approach, based on EDAS (evaluation based on distance from average solution) method allows decision-makers to consider multiple criteria, account for uncertainty and vagueness, and make informed choices based on a wider range of factors. The main goal of this study is to introduce complex fuzzy (CF) rough averaging aggregation and geometric aggregation operators and embed these operators in EDAS to obtain remarkable results in MCGDM. Furthermore, we propose the CF rough weighted averaging (CFRWA), CF rough ordered weighted averaging (CFROWA), and CF rough hybrid averaging (CFRHA) aggregation operators. Additionally, we present the concepts of CF rough weighted geometric (CFRWG), CF rough ordered weighted geometric (CFROWG), and CF rough hybrid geometric (CFRHG) aggregation operators. A new score function is defined for the proposed method. The basic and useful aspects of the explored operators were discussed in detail. Next, a stepwise algorithm of the CFR-EDAS method is demonstrated to utilize the proposed approach. Moreover, a real-life numerical problem is presented for the developed model. Finally, a comparison of the explored method with various existing methods is discussed, demonstrating that the exploring model is more effective and advantageous than existing approaches. © The Korean Institute of Intelligent Systems