Author(s)

Lijun Liu ¹, Kaixing Liu ¹, Meng Deng ²

Affiliation(s)

¹ College of Mechanical an Electrical Engineering, Shaanxi University of Science & Technology, Xi'an, Shaanxi, 710021, China
² College of Physics, Shaanxi University of Science & Technology, Xi'an, Shaanxi, 710021, China

Corresponding Author

Lijun Liu

ABSTRACT

The third-party logistics company that uses a centralized supply model to supply parts to automakers in a timely manner is an important part of the automotive supply chain. In order to improve customer service and control cost, the accurate forecasting of the third-party company safety stock becomes the core concern of enterprises. For the limited data samples, low linear correlation and high latitude in the third-party logistics inventory forecast, a safety stock forecasting model based on LS-SVM was proposed. An example analysis was performed on the historical data of a third-party automobile logistics center to verify the accuracy and sensitivity of the model.

KEYWORDS

LS-SVM; Supply chain, Safety stock, Forecasting

CITE THIS PAPER

Lijun Liu, Kaixing Liu, Meng Deng, A Safety Stock Forecasting Model of the Third-Party Logistics Based on Least Squares Support Vector Machine. Industrial Engineering and Innovation Management (2025) Vol. 8: 22-31. DOI: http://dx.doi.org/10.23977/ieim.2025.080103.

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