Hesitant Fuzzy Linguistic TODIM Method And Its Application In Green Supplier Selection

The choice of long term stable suppliers is the primary problem of building green supply chain under the green supply chain management mode.The problem of green supplier selection has a direct impact on the competitiveness of enterprises in the market.It is an urgent problem that the enterprise how to grasp the changeable internal and external environment and according to their own needs to determine the reasonable evaluation index and choose the right green supplier.To coordinate with economic benefits,green supplier selection take the environmental factors into account and given a certain weight.Green supplier selection process should not emphasize the environmental factors too much,nor emphasize the economic benefits too much,only by coordinating the development of the two,can promote long-term cooperation between enterprises and suppliers.Green supplier selection is a very complex decision problem.Due to the complexity of green supply chain system and the uncertainty,fuzziness and hesitation of human thinking,the evaluation of green suppliers will be affected by uncertain factors,which makes it difficult for some evaluation indexes to be characterized by exact values.In order to be more in line with the decision maker's way of thinking and cognitive model,the language is used to describe the attribute value.With the rapid development of science and technology,many decision problems in life becomes increasingly complex,it is very difficult to solve these problems by relying solely on a decision maker.Multiple decision makers make decisions together can not only reduce the errors,but also improve the accuracy of decisions.Thus,it is of great significance to apply the hesitant fuzzy linguistic multi-attribute group decision making method in the selection of green suppliers.This paper further research on the related theories and methods of hesitant fuzzy linguistic multi-attribute group decision making and its application in green supplier selection based on the previous studies,the main research contents are as follows:(1)On the premise of systematically introducing the related concepts of hesitant fuzzy linguistic term sets,a hesitation index of hesitant fuzzy linguistic term sets is defined,which can better measure the hesitation of decision maker in the evaluation process.On the basis of the hesitation index,a hesitant fuzzy linguistic distance measure is improved,then a method for comparing hesitant fuzzy linguistic term sets is defined by using the hesitant fuzzy linguistic symbol distance.(2)The hesitant fuzzy linguistic TODIM(an acronym in Portuguese of interactive and multi-criteria decision making)method is proposed to solve multi-attribute group decision making problem.The maximum deviation method is extended to the hesitant fuzzy linguistic environment to determine the attribute weights of each expert.In the case of incomplete expert weight information,a multi-objective programming model is established by maximizing the importance of preference relations,and the expert weights are solved after being transformed into single objective programming.Then,the comprehensive index weight vector is obtained by aggregating the expert weight vector and the attribute weight vector of each expert,thus,the group decision matrix is obtained by using the hesitant fuzzy linguistic weighted average operator.Finally,the classical TODIM method is extended to hesitant fuzzy linguistic environment,and then get the ranking of alternatives.(3)Based on the existing green supplier selection research,the green supplier evaluation index is constructed,which includes the company's cost factors,the company's product factors,the company's service factors,the company's organizational factors and the company's environmental factors.By using the hesitant fuzzy linguistic TODIM method to solve the problem of green supplier selection,evaluate the four green suppliers of the furniture company to select the most consistent with the company's development of green suppliers.The effectiveness and flexibility of the proposed method are verified by comparison with the hesitant fuzzy linguistic TOPSIS(technique for order preference by similarity to an ideal solution)method.