Selection Of Power Battery Third-Party Reverse Logistics Enterprise Based On Hybrid Multi-Attribute Group Decision

In recent years,new energy vehicles have been developing rapidly.After only a few years of service life,power batteries has entered the peak period of decommissioning.However,the waste power battery has brought serious environmental pollution,and the country attaches great importance to the reverse logistics recovery of waste power battery.Under the advocacy of a series of national professional recycling policies,automobile manufacturers are looking for suitable partners to share the recycling business of waste power batteries.Third-party recycling enterprises provide professional reverse logistics services,which can make up for the limited resources of automobile enterprises,focus on the development of core business,and improve core competitiveness.It is a realistic choice for the automobile manufacturers to find appropriate third-party recycling enterprises.Under such a background,this paper studies and analyzes the selection of power battery third-party reverse logistics recycling enterprises,and proposes a hybrid multiattribute group decision-making method considering expert risk preference.The main research results are as follows:(1)A hybrid multi-attribute system for evaluation of power battery third-party reverse logistics enterprises is established.Based on the perspective of power battery manufacturing enterprises,the system summarizes 19 important attributes and characteristics of third-party reverse logistics enterprises from five aspects of cost factor,ecological benefit,technological level,safety level and logistics service quality,which provides an important basis for comprehensive investigation,evaluation and selection of third-party partners.(2)Based on the selection of power battery third-party reverse logistics enterprises,a hybrid multi-attribute group decision making method considering expert risk preference is proposed.This method is divided into two stages: hybrid multi-attribute data transformation stage and expert group decision stage.In this method,expert risk preference is considered in both stages.In the transformation stage of mixed multi-attribute data,the mixed data is transformed into unitary data,and a scoring function based on risk preference is proposed to transform intuitionistic fuzzy numbers into exact numbers.In the stage of expert group decision making,the improved prospect theory is introduced,and the improved prospect value of each expert is obtained.A subjective and objective combined weight model based on improved entropy weight method and G1 method is constructed to solve attribute weight.The weight of experts is determined from two perspectives: the hesitation degree of expert decision information and the reliability of prospect value.Finally,the comprehensive prospect value of each scheme is calculated.(3)An example of an automobile manufacturer choosing a third party recycler is studied.The comprehensive improvement prospect value is calculated,and the optimal third party recycler is selected according to its size,which verifies the effectiveness and practicability of the proposed method.