Unbalanced double hierarchy linguistic group decision-making method based on SWARA and S-ARAS for multiple attribute group decision-making problems

Curriculum evaluation shoulders the important task of measuring the realization of talent cultivation. Effective curriculum evaluation enables the school to optimally arrange courses and improve the overall quality of students. To implement the curriculum evaluation effectively, this paper constructs a multiple attribute group decision-making (MAGDM) method according to the characteristics of curriculum evaluation. In view of the nonlinearity and hesitation of decision maker's cognition, unbalanced double hierarchy linguistic term sets (UDHLTSs) are utilized to fully represent the individual cognition of decision makers. Based on this, a novel MAGDM method with UDHLTSs is proposed. Firstly, to facilitate the analysis and treatment of UDHLTSs, the basic theories of UDHLTSs are perfected or complemented. Based on this, the unbalanced double hierarchy linguistic aggregation operator is defined and its properties are analyzed. Secondly, the weight determination method based on SWARA model is proposed to determinate the importance of each evaluation index under UDHLTSs environment. Thirdly, given the appetite of different decision-makers towards risk, an extended S-ARAS method is proposed based on S-utility function. Finally, to illustrate its effectiveness and rationality, the proposed method is applied in the case study of curriculum evaluation in university and compare with other methods.