The Research On Multiple-attribute Decision Making Methods Based On Single-valued Neutrosophic Hesitant Fuzzy Information And Its Application In Low-carbon Logistics Park Site Selection

With the rapid development of the e-commerce Internet,online shopping has been enthusiastically sought after by people,the logistics industry has also risen rapidly.Logistics have promoted economic growth,which occupy an prominent place in national economy development.However,as an indispensable part of the logistics industry,logistics parks have many difficult problems.Generally speaking,it occupies a large area and the construction investment cost is high.Once completed,it is not easy to relocate,and environmental problems are becoming more and more serious in current society.Building a green,low-carbon and environmentally friendly logistics park is the primary task of the logistics industry.“Low energy consumption and high efficiency” has become a low-carbon basic guidelines for planning and construction of logistics parks.The location of a low-carbon logistics park can be regarded as a multi-attribute group decision-making problem.Generally,many decision makers replace the corresponding evaluations on a limited number of alternatives under the influence of different elements,and process the relevant evaluation information through scientific decision-making methods,so as to sort the different alternatives and make a reasonable choice.Due to the ambiguity of people's cognition and the complexity of the decisionmaking environment,it is more reasonable to transform decision-making process in a fuzzy environment.As a generalization of fuzzy sets theory,neutrosophic hesitant fuzzy sets have unique advantages in dealing with incomplete,uncertain and inconsistent fuzzy information,which are denoted by truth,indeterminacy,and falsity membership hesitant functions,it allows element membership to be expressed as a set of features that are several possible values in [0,1],which fully solves the problem of hesitation and uncertainty or inconsistency in the evaluation of information by decision makers.This paper mainly studies the multi-attribute group decision-making problem of low-carbon logistics park site selection under the environment of single-valued neutrosophic hesitant fuzzy sets.The main research contents are as follows:(1)Sorting out the relevant definitions of the existing distance measures of the single-valued neutrosophic hesitant fuzzy sets,and discovering the shortcomings and deficiencies-inconsistency of the membership cardinality.It is usually used to increase the virtual value to obtain the same cardinality in the process of the calculation.The final result will cause a certain deviation.In order to preserve the original data information as much as possible,this paper also considers the difference and volatility of single-valued neutrosophic hesitant fuzzy numbers,and proposes new single-valued neutrosophic hesitant Hamming distance,Euclidean distance,and generalized distance measures and its weighted forms.It is need to verifies that the proposed new distance measure satisfies the four characteristics of distance measure.Based on the correlation between distance measure and similarity measure,a new singlevalued neutrosophic hesitant fuzzy similarity measure is also proposed.These laid the theoretical foundation for the full contents research.(2)In the actual decision-making situation,the weight of the attribute criterion are difficult to obtain directly,and the weight information given by the decision maker through subjective preference will have a certain degree of influence on the final alternatives selection.Therefore,the study of completely unknown attribute weights is more in line with current complex decisionmaking problems.This paper aims at the multi-attribute group decisionmaking problem of obtaining unknown attribute weights in the single-valued neutrosophic hesitant fuzzy environment,and proposes a group decision method based on the single-valued neutrosophic hesitant fuzzy extension VIKOR under a new distance measure.The main purpose is to use the new distance measure to construct a maximum deviation optimization model to determine the weight of unknown attributes.The VIKOR method takes into account both maximizing group utility and minimizing individual regrets,and at the same time considers the subjective preferences of decision makers to evaluate the optimal result.The model method is applied to the actual problem of low-carbon logistics park site selection.Further compare and analyze the calculation results of the traditional distance measures,the extended TOPSIS method and the extended VIKOR method applied to actual cases,to prove the effectiveness and advantages of the proposed method,and the stability of the proposed model method through sensitivity analysis.(3)The power partitioned Heronian mean operator,the power geometric partitioned Heronian mean operator is extended to the environment of singlevalued neutrosophic hesitant fuzzy sets,single-valued neutrosophic hesitant fuzzy power partitioned Heronian mean operator and single-valued neutrosophic hesitant fuzzy power geometric partitioned Heronian mean operator and their weighted forms are proposed,and four major characteristics satisfied by these operators are explored and proved: Permutation invariance and Idempotency,Boundedness and Monotonicity.A single-valued neutrosophic hesitant fuzzy weighted power partition Heronian mean operator decision-making method under new distance measure is proposed to solve the multi-attribute group decision-making model in which there is a correlation between the two attributes.A MAGDM method based on the proposed operators is applied to the location problem of low-carbon logistics parks.The results of other literature methods and the extended VIKOR method mentioned above are compared and analyzed to illustrate the feasibility and rationality of the method proposed in this article.