| With the development of society and the prosperity of the economy,the problems that people have to face become more and more complex.When faced with decision-making issues,the difficulty increases.Efficient decision-making and sound scientific analysis of the impact of multiple factors are essential.Multi-attribute decision problem is widely used in life and it is an important component of decision analysis.There are many methods of multi-attribute decision making,and hierarchical analysis is an effective and convenient way to deal with some of the more complex problems.However,the Hierarchical Approach does not fully meet the problems encountered in people’s decision making.So people incorporated the concept of fuzziness in the hierarchical analysis method,which is a new decision making method called fuzzy hierarchical analysis.Fuzzy analytic hierarchy process is more consistent with the fuzziness of human thinking and judgment,and also with the fuzzy nature of things themselves.When using fuzzy hierarchical analysis for decision making,it is necessary to establish a two-two comparison expert fuzzy complementary judgment matrix,which is directly related to the reasonableness of the weight ordering vector.Only a rational construction of the judgment matrix can guarantee that the weight vectors truly reflect the objective ranking of importance among decision factors.And the reasonableness of the judgment matrix can be measured by its consistency.So when people use fuzzy hierarchical analysis to deal with complex decision problems,the detection and correction of the consistency of the expert judgment matrix is the focus.The traditional fuzzy hierarchical approach does not have a consistency test and correction of the judgment matrix,it transforms the judgment matrix into fuzzy consistency matrix and solves for the weight vector,which has no scientific basis.Some of the literature has proposed fuzzy complementary judgment matrix consistency tests and fixes for fuzzy hierarchical analysis.But in the face of complex decision problems,the fuzzy complementary judgment matrix has a large order of magnitude and cannot guarantee the efficiency of matrix consistency correction.The issue of fuzzy complementary judgement matrix consistency needs to be focused on,and the study of a method that enables fast and accurate correction of fuzzy complementary matrix consistency is a trend in the development of multi-attribute decision-making.In the introduction to this paper,the relevant background of multi-attribute decision making is outlined.The reasons for the birth of the fuzzy hierarchical approach are then elaborated based on the inadequacy of the hierarchical approach.The basic principles and algorithmic steps of fuzzy hierarchical analysis and the advantages and disadvantages of fuzzy hierarchical analysis and hierarchical analysis are summarized.Next,the test criteria for the consistency of the fuzzy complementary judgment matrix and the consistency correction method were studied and analyzed.This paper adopts a combination of exact value,interval value and triangular fuzzy number to preserve the preferences and fuzzy nature of expert judgment,and uses the 0.01-0.99 scale with good linearity to construct the fuzzy complementary judgment matrix,which optimizes the FAHP to some extent.According to the properties of fuzzy consistency matrix,a nonlinear constrained programming problem for consistency correction of fuzzy complementary judgment matrix based on least square method is presented.In order to preserve as much of the original information of the fuzzy complementary judgment matrix as possible,a least squares model of the modified judgment matrix and the original judgment matrix is built to limit the magnitude of the correction of matrix consistency.And combined with the group intelligence optimization algorithm PSO to solve the above constrained planning problems.Therefore,this method optimizes the consistency of the judgment matrix while preserving the expert judgment information on the judgment matrix as much as possible,so that the weight ordering vector is obtained.Finally,the model was applied to the evaluation of pig breeding standardization and the weights of evaluation indicators were calculated.Scoring and grading is done in conjunction with the affiliation function of the evaluation indicator and the European approximation.Selected pig farm examples were evaluated for standardization of pig breeding to demonstrate that the model is efficient and reliable. |
