## 2 Materials and Methods
### Proposed Approach
#### 2.1.1 AHP and FCE  
The AHP has become a multi-criteria method that is widely used by decision makers. It is used in many fields, such as supply chain evaluation, economy and planning, energy policy and resource allocation, human resource management, prediction, and so on. The AHP is mainly used as an auxiliary decision-making tool. Only when it is organically combined with other methods can it be used effectively. From the existing research results,other methods that have been used in combination with the AHP include fuzzy set theory, fuzzy logic, digital planning, cost-benefit analysis, and so on. FCE transforms a qualitative evaluation into a quantitative evaluation in accordance with the membership theory of fuzzy mathematics. It provides clear results and has a strong level of systematicness. FCE can solve fuzzy and difficult-to-quantify problems more effectively, and it is suitable for solving various uncertain problems. When there are variables that are thought to have been given numerical values through their experience as evaluation indicators, FCE can be considered; for instance, if they have been used to determine whether the service quality is excellent, whether the agricultural products are fresh, or whether the quality is safe. FCE effectively combines subjective human experiences with the rigorous reasoning of mathematical theory. It is suitable for research use in the fields of social investigation, quality assessment, market consultation, educational reform, the promotion of enterprising employees, evaluation, and promotion. Fresh agricultural produce supply chain platform service quality evaluation indexes have a certain degree of fuzziness and uncertainty, and their specific scoring values are obtained through the analysis of research results relating to consumer satisfaction. For the comparative analysis of these evaluation methods, we chose to adopt and improve the more mature general methods in operations research--the hierarchical analysis and fuzzy comprehensive evaluation method. Moreover, we combined the advantages of both for comprehensive analysis to try and produce a more scientific and reasonable quantitative evaluation of fuzzy objects through effective mathematical means. This was carried out in order to effectively avoid the two when solving calculations. The shortcomings of both methods in terms of scientific and complexity were effectively avoided. Due to the aforementioned advantages of the FCE method, this paper used the FCE method to carry out comprehensive evaluation research. Fuzzy comprehensive evaluations are based on concepts of fuzzy mathematics and the principle of fuzzy relation composition. It is a method that quantifies some factors which have unclear boundaries and are difficult to quantify, then, it comprehensively evaluates the subordination level of the evaluated aspects from multiple factors. The basic principles of this method are as follows: first, a factor set and comment set of the evaluated object are determined; then, the weight of each factor and its membership vector are determined, and the fuzzy evaluation matrix is obtained; finally, the fuzzy evaluation matrix and the weight vector of the factors are fuzzy calculated and normalized, thus enabling the FCE results to be obtained. Considering the influence of operation difficulty, calculation complexity, and other factors, the objective weighting method was not suitable for use in this study. This paper used the AHP method to determine the weight of each index. The analytic hierarchy process was proposed by [PERSON], an expert in operational research at the University of Pittsburgh, in early the 1970s. The advantages of this method include the simplicity of the calculation, the clarity of the results, and the clarity of the logic. This combination of qualitative and quantitative methods can deal with many practical problems that cannot be solved using traditional optimization techniques. It can be widely used, and it is a practical MCDM method.