Since the interval complementary preference relationship can more concisely and intuitively describe the decision maker’s uncertain cognition,this paper proposes three multi-attribute group decision-making methods based on the interval complementary preference relationship.The proposed methods take into account the consistency of decision makers’ preferences and the consensus among decision makers’ preferences.In addition,the methods are applied to rural tourism development evaluation.It mainly includes the following research contents:This paper studies the ordinal consistency,additive consistency,mixed consistency and consensus of interval complementary preference relations.Firstly,based on the ordinal consistent interval complementary preference relations,this paper proposes a multi-attribute group decisionmaking method.For the case of ordinal inconsistency,this paper presents algorithms for identifying and adjusting ordinal consistency based on the directed graph theory,and an ordinal consensus model is constructed.Secondly,by discussing the additive consistency and consensus of the interval complementary preference relations,a multi-attribute group decision-making method based on the complete additive consistency interval complementary preference relations is proposed.Given the limitations of the existing definitions,redefine the additive consistency of the interval complementary preference relations.Based on this,an optimization model is constructed to discuss the incompleteness,consistency and consensus of the interval complementary preference relations.Thirdly,this paper proposes a multi-attribute group decisionmaking method based on the mixed consistent interval complementary preference relations.For ordinal consistency and acceptable additive consistency,models for adjusting ordinal consistency and acceptable additive consistency are constructed.Based on this,models for adjusting mixed consistency and consensus are constructed.Finally,the three methods are applied to rural tourism development evaluation,and comparative analysis and sensitivity analysis are carried out to verify the rationality and feasibility of the proposed method. |