Academic Journal of Computing & Information Science, 2022, 5(5); doi: 10.25236/AJCIS.2022.050512.
Yunuo Chen1, Yingjian Zhu1, Xuemei Tian2
1School of Mathematics and Statistics, Hubei Normal University, Huangshi, Hubei, China
2School of Computer and Information Engineering, Hubei Normal University, Huangshi, Hubei, China
Aiming at the raw material ordering and transportation process of production enterprises, this paper first selects the supply index and obtains 56 suppliers with large supply volume. Then, with the help of entropy method, 56 suppliers are ranked by supply variance, order quantity, payment rate and supply frequency as decision variables. In order to obtain the most economical ordering plan, the data of order quantity and supply quantity are mined, and the categories of suppliers are further divided into stable suppliers, potential emergency suppliers and general emergency suppliers. By accumulating the production capacity from high to low among 50 suppliers one by one, the threshold larger than the historical average production capacity of 670397m ³is found. Finally, it is determined that only 39 suppliers can meet the production conditions.
Data mining, Planning problem, BP neural network, Entropy weight method
Yunuo Chen, Yingjian Zhu, Xuemei Tian. Research on Enterprise Raw Material Ordering and Transportation Based on Index Analysis and Entropy Method. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 5: 91-96. https://doi.org/10.25236/AJCIS.2022.050512.
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