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Decision Model of Ordering and Transportation of Raw Materials Based on Big Data

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DOI: 10.23977/jnca.2021.060107 | Downloads: 13 | Views: 1102

Author(s)

Jin Wang 1, Shujian Gao 1, Yuan Wang 1

Affiliation(s)

1 Beijing Jiaotong University, Beijing, 100044

Corresponding Author

Yuan Wang

ABSTRACT

This paper mainly studies the decision-making of enterprises for different suppliers and forwarders. Firstly, this paper preprocesses the given data and excludes the data with order quantity and supply quantity of 0. Then, in the quantitative analysis, the core indicators of decision-making are refined and summarized as: effective supply weeks, effective average supply quantity and effective residual. In quantitative analysis, the core indicators of decision-making are refined and summarized as: effective supply weeks, effective average supply quantity and effective residual. For these three core indicators, firstly, the effective residual is studied. In order to make vertical comparison between different suppliers, we first normalize their supply volume data before calculating the effective residual, so as to achieve the purpose of consistent comparison. Then, the square sum of the three indicators is normalized to make the three indicators consistent. Then the TOPSIS entropy weight model is called, and the corresponding ranking results are obtained through SPSS data analysis software and related formulas.

KEYWORDS

TOPSIS entropy weight model, Multiobjective linear programming, SPSS

CITE THIS PAPER

Jin Wang, Shujian Gao, Yuan Wang. Study on Characteristics and Practice of TCM nursing in Anorectal Department Based on TCM Syndrome Differentiation System. Journal of Network Computing and Applications (2021) 6: 31-35. DOI: http://dx.doi.org/10.23977/jnca.2021.060107.

REFERENCES

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[2] Jia Xiaoqiang. Time series data mining algorithm based on multi-objective decision [J]. Electronic design engineering, 2021, 29 (17): 45-49. Doi: 10.14022/j.issn1674-6236.2021.17.010.
[3] Liang Qiuping, Yan Xueying. Comprehensive evaluation of nutritional quality of different sweet cherry varieties based on entropy weight TOPSIS method [J]. Food research and development, 2021, 42 (16): 59-64.

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