Application Of Bijective Soft Set Evaluation Model With Info Redundancy In Evaluating Reverse Logistics Performance

With the rapid and booming development of the logistics industry in China, the word of "Reverse logistics" appears in the vision of people more frequently, more and more enterprises and related institutions began to realize the importance of the reverse logistics. In the global renewable energy has been depleted of today, various social resources become scarce, China put forward the sustainable development path, the development of circular economy mode policy, one of the first precondition is the development of a perfect reverse logistics management system. As an important part of enterprise management of reverse logistics, reverse logistics performance evaluation plays a significant role. Therefore, it is necessary to strengthen the study on Evaluation of enterprise reverse logistics performance, thus scientifically and reasonably to dig out the key indicators of enterprise reverse logistics performance evaluation, redundant indexes eliminated and evaluation of little relevance, reduce the objectivity of evaluation results and one sidedness, sustainable development, and ultimately realize enterprise resource intensive utilization and social economy.At present, the evaluation method of enterprise reverse logistics performance can be roughly divided into the traditional evaluation methods and mathematical evaluation of emerging methods of two kinds of enterprise reverse logistics performance evaluation, traditional methods are cluster analysis method, expert evaluation method,the method of limited factors, subjective weighting method, this kind of method is mostly determined by quantitative data and analysis method based on. However, in the process of enterprise reverse logistics performance evaluation will inevitably relates to the environmental changes, such as the dynamic index of analyzing and dealing with the uncertain factors, the face of the fuzzy information processing, incomplete, the traditional evaluating method is no longer applicable.The purpose of this article is to solve the uncertainty factors of the performance evaluation of enterprise reverse logistics. The main method is use the emerging mathematical evaluation method to deal with the evaluation of the fuzziness qualitative factors. In view of this, this article introduced the existence of information redundancy in the wrong bijection soft collection evaluation model. Making it in the uncertainty environment to find out the soft set processing method to deal with incomplete andimprecise information. Improving the scientific and effectiveness of the performance evaluation of enterprise reverse logistics. In addition, to obtain a relatively comprehensive index evaluation system to the enterprise reverse logistics performance,the construction of index system also became one of the research content of this article.In order to get a relatively complete collection of indicators, we have done the following work. First of all, the article analyses the predecessors’ research to given the summary, to ensure that covers all of the indicators. Secondly, in order to make the index system is relatively simple; the article introduced the KPI key performance index method to modify the index system. In addition, according to the macroscopic characteristics and research environmental of reverse logistics, the article made further processing on index system. Finally, using bijection soft sets decision-making system about reduction algorithm to extract the several key indicators that have the maximum correlation between with the evaluation results. Thus based on KPI key performance index system and the bijection soft sets decision-making system valuation model, this paper using 20 reverse logistics enterprise sample data to the empirical analysis, the result prove the usability and effectiveness of the model, and some management experience and enlightenment are given.The research results show that, the evaluation model that based on the Key Performance Indicator and bijective soft set decision system can less limited the sample data. It could parametric processing the uncertain data, excavate the key index information effectively and Get the index weight by calculating the dependency of quantitative indicators. The analysis results of the 20 enterprises in the sample data show that, the four indicators, total assets turnover, reverse service capability, customer satisfaction and the degree of enterprise information are the key factors that affect the reverse logistics performance of enterprise.