Paper
16 December 2022 A framework for purchasing and transferring materials for enterprise production
Author Affiliations +
Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 125001G (2022) https://doi.org/10.1117/12.2662664
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China
Abstract
In a highly competitive market, it is critical for companies to effectively reduce raw material procurement and forwarding costs in the production of their products. Based on the data of suppliers and forwarders, we optimize all the details of the procurement process and minimize the procurement cost of enterprises through a complete solution called APSA. APSA first selects some of the most critical suppliers from all supplier data using multiple evaluation methods combined with the TOPSIS evaluation model. In this process, three attributes, “Time-weight Mean”, “Order Quantity Variance” and “Trading Stability Factor” were defined by us to evaluate each supplier more comprehensively from multiple perspectives. For the prediction of forwarder data, the rational analysis of the periodical features of each forwarder is used first. Then ARIMA and LSTM are applied, respectively, with the different data types. Finally, reasonable multi-objective optimization equations are established, and the optimal procurement and transfer solution is solved by the simulated annealing algorithm.
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Ke Xie, Ruijia Ma, Yanjia Luo, Peng Li, and Jie Wu "A framework for purchasing and transferring materials for enterprise production", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 125001G (16 December 2022); https://doi.org/10.1117/12.2662664
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KEYWORDS
Data modeling

Raw materials

Algorithms

Optimization (mathematics)

Neural networks

Autoregressive models

Process modeling

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