Optimization of ordering and forwarding solutions for manufacturing enterprises based on decision model

Xiao Yu

doi:10.1117/12.2641923

10 November 2022 Optimization of ordering and forwarding solutions for manufacturing enterprises based on decision model

Xiao Yu

Author Affiliations +

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 1234803 (2022) https://doi.org/10.1117/12.2641923
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

This paper establishes a multi-objective integer programming model considering economic and safety aspects. The time series model predicts the loss of goods by forwarders for the forwarding decision, and dynamic planning is used to solve the forwarding solution with the lowest loss of goods. Firstly, the data are preprocessed by ADF test and quadratic isolated forest algorithm, raw material preference weights are set according to Friedman test and transaction mean, and decision tree model classifies suppliers, and finally, 50 most important suppliers are selected by ranking through structural entropy weight -Topsis comprehensive evaluation method; based on the marginal decreasing effect, a strategic-large supplier interaction function is established, and the minimum number of suppliers is solved to be 35, and the corresponding number of A, B and C suppliers are selected according to the ranking and quota allocation. Then, the minimum number of suppliers to meet the production demand of the enterprise is determined by the ordering scheme decision model based on multi-objective integer planning.

Citation Download Citation

Xiao Yu "Optimization of ordering and forwarding solutions for manufacturing enterprises based on decision model", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 1234803 (10 November 2022); https://doi.org/10.1117/12.2641923

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