Spherical fuzzy Dombi power Heronian mean aggregation operators for multiple attribute group decision-making - Zhang, Huiyuan; Wei, Guiwu; Chen, Xudong (Computational & applied mathematics, 2022)
As a new improvement of fuzzy sets (FSs), spherical fuzzy sets (SFSs) can provide a wider space for decision-makers (DMs) to express their preference information. Spherical fuzzy aggregation operators are a vital tool for multiple attribute group decision-making (MAGDM) in spherical fuzzy environment (SFE). Thus, the main work of this paper is to develop some new aggregation operators (AOs) to fuse spherical fuzzy information. First, based on Dombi operators and Heronian mean (HM) operator, we develop spherical fuzzy Dombi Heronian mean (SFDHM) operator, spherical fuzzy Dombi weighted Heronian mean (SFDWHM) operator, spherical fuzzy Dombi geometric Heronian mean (SFDGHM) operator and spherical fuzzy Dombi weighted geometric Heronian mean (SFDWGHM) operator. Second, considering the influence of extreme data on decision results, we utilize the merit of power average (PA) operator to further develop spherical fuzzy Dombi power Heronian mean (SFDPHM) operator, spherical fuzzy Dombi weighted power Heronian mean (SFDWPHM) operator, spherical fuzzy Dombi power geometric Heronian mean (SFDPGHM) operator and spherical fuzzy Dombi weighted power geometric Heronian mean (SFDWPGHM) operator. In the meantime, we discuss some desirable properties of these operators. Furthermore, we establish some novel MAGDM methods to aggregate spherical fuzzy numbers (SFNs) by utilizing the presented AOs. Finally, an example of enterprise resource planning (ERP) systems selection is employed to verify the applicability of the established approaches, and the effectiveness and superiority of the designed methods are proved by further comparison with the existing methods.