Fuzzy Multicriteria Decision-Making Analysis of Agricultural Product Logistics in Agricultural Economic Management

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Abstract

The purpose is to establish a logistics supplier evaluation and selection model for green supply chain, which can effectively take into account the environmental problems, while the enterprise economy is developing. The logistics supplier evaluation index system is established under the background of green logistics based on fuzzy theory and multicriteria decision-making theory. The green competitiveness index is innovatively introduced into the system. Moreover, a fuzzy hybrid multicriteria decision-making method model is established based on the deficiency of the current supplier evaluation and selection methods, so as to select logistics suppliers; finally, the established logistics supplier evaluation and selection method is applied to real enterprises for example verification. The results are as follows. The direct relationship matrix is obtained according to the opinions of the expert group, and the relationship matrix is defuzzified and standardized to obtain the clear value of the secondary index. Finally, the fit between the evaluation results of the five logistics companies and the positive and negative ideal values is calculated. According to the principle of maximum fit, the evaluation priority of the five companies is 4 > 3 > 2 > 5 > 1. Thereby, taking the fuzzy multicriteria decision-making analysis method as the evaluation model has high reference value for the evaluation of green logistics companies, solves the problem of how production and sales enterprises choose green logistics suppliers, fully meets the needs of enterprises and governments that focus on the green degree of suppliers in the supply chain, and can effectively promote the efficient operation of green supply chain management.

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APA

Tang, M., & Wang, Z. (2021). Fuzzy Multicriteria Decision-Making Analysis of Agricultural Product Logistics in Agricultural Economic Management. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/1730594

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