Several Fuzzy Multi-attribute Decision Making Methods And Their Application Analysis

Due to the development of global informationization,the complexity of the objective environment and the limited knowledge of investors,decision makers often face great ambiguity and uncertainty,and they often need reasonable and practical decision-making methods to assess the projects.But the current quantitative methods usually ignore the uncertainty of the indicators,the evolving fuzzy theory provides a powerful tool for dealing with this problem.In this paper,we use the qualitative and quantitative decision-making methods to solve the fuzzy multi-attribute decision problem,which can solve the uncertainty of the attribute index and the difficulty of estimating the parameters in the model.We study the following several aspects in this paper:(1)Developing the decision evaluation methods based on Pythagorean fuzzy variables.Firstly,Based on Archimedean T mode and S model,several special Archimedean T modes and S models are proposed in Pythagorean fuzzy environment,such as algebraic T mode and algebraic S mode,Hamacher T mode and Hamacher S mode,Frank T mode and Frank S mode.Secondly,on the basis of Hamacher T mode and Hamacher S mode,the rules of Hamacher operator in Pythagorean fuzzy environment are defined,and several Pythagorean fuzzy Hamacher information aggregation operators are proposed,and two different methods for solving the decision-making problems are given.Thirdly,on the basis of Frank T mode and Frank S mode,the rules of Frank operator in Pythagorean fuzzy environment are defined,and several Pythagorean fuzzy Frank information aggregation operators are developed,and two different methods for solving the decision-making problems are proposed.Finally,for the evaluation problem that the attribute weight information is unknown and attribute values is in the form of Pythagorean fuzzy variables,based on the LINMAP method and TOPSIS method,an approach is developed to solve decision-making problems when the expert and attribute weight is known,partly known and completely unknown.(2)Developing the decision evaluation methods based on hesitant Pythagorean linguistic fuzzy variables.Firstly,based on the hesitant fuzzy set and the Pythagorean linguistic fuzzy set,the hesitant Pythagorean fuzzy linguistic set(HPFLSs)is defined.Secondly,for the decision evaluation problem that the attribute is mutual independent and the attribute values take the form of hesitant Pythagorean fuzzy linguistic variables,some hesitant Pythagorean fuzzy linguistic information integration operators are defined,and two approaches for the decision selection are developed on the basis of these operators.Thirdly,for the decision evaluation problem that the attribute is correlative and attribute values is in the form of hesitant Pythagorean fuzzy linguistic set,the hesitant Pythagorean fuzzy linguistic Power Einstein weighted arithmetic average(HPFLPEWA)operator and hesitation Pythagorean fuzzy linguistic Power Einstein(HPFLPEWG)operator are developed.Based on HPFLPEWA and HPFLPEWG operators,two approaches for the decision selection are developed.Finally,for decision evaluation problem that the attribute is unknown and attribute values is in the form of hesitant Pythagorean fuzzy linguistic set,an extended grey relational analysis(GRA)method is developed to solve decision evaluation problem under hesitant Pythagorean fuzzy linguistic environement.(3)Developing the decision evaluation methods based on interval Pythagorean fuzzy linguistic variables.Firstly,based on the interval Pythagorean fuzzy set and the Pythagorean linguistic fuzzy set,the interval Pythagorean fuzzy linguistic set is defined.Secondly,for the decision evaluation problem that the attribute is mutual independent and the attribute values take the form of interval Pythagorean fuzzy linguistic variables,some interval Pythagorean fuzzy linguistic information integration operators are defined,based on these operators,two approaches for the decision selection are developed.Thirdly,for the decision evaluation problem that the attribute is correlative and attribute values is in the form of interval Pythagorean fuzzy linguistic set,the interval Pythagorean fuzzy linguistic Choquet weighted arithmetic average(IVPFLCWA)operator and the interval Pythagorean fuzzy linguistic Choquet weighted geometric average(IVPFLCWG)operator are developed,an approach for decision evaluation is developed on the basis of these operators.Finally,for decision evaluation problem that the attribute weight is unknown and attribute values is in the form of interval Pythagorean fuzzy linguistic set,based on the TOPSIS method,an approach for decision evaluation is developed.(4)Developing the decision evaluation methods based on interval intuitionistic linguistic variables.Firstly,based on interval intuitionistic linguistic variables and Frank aggregation operators,the rules of Frank operators in the interval intuitionistic linguistic environment are defined.Secondly,for the decision evaluation problem that the attribute is mutual independent and the attribute values take the form of interval intuitionistic linguistic variables,several interval intuitionistic linguistic Frank information aggregation operators are developed.Based on the above-mentioned operators,the decision-making method is proposed in the interval intuitionistic linguistic fuzzy environment.Finally,for the decision evaluation problem that the attribute is existing priority relationship and attribute values is in the form of interval intuitionistic linguistic variables,the interval intuitionistic linguistic Frank Prioritized weighted arithmetic average(IVILFPWA)operator and the interval intuitionistic linguistic Frank Prioritized weighted geometric average(IVILFPWG)operator are defined.An approach for the decision making evaluation is developed on the basis of these operators.(5)Developing the decision evaluation methods based on uncertain interval membership linguistic variables.Firstly,based on the uncertain linguistic set and the interval fuzzy set,uncertain interval membership linguistic set is introduced.Secondly,for the decision evaluation problem that the attribute is mutual independent and the attribute values take the form of uncertain interval membership linguistic variables,several uncertain interval membership linguistic information aggregation operators are developed,and two approaches for the decision-making evaluation are developed on the basis of these operators.Thirdly,for the decision evaluation problem that the attribute is correlative and attribute values is in the form of uncertain interval membership linguistic set,several uncertain interval membership linguistic Einstein information aggregation operators are defined.An approach for the decision-making evaluation is developed on the basis of these operators.