Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Truck Weight Estimation using Operational Statistics at 3rd Party Logistics Environment

운영 데이터를 활용한 제3자 물류 환경에서의 배송 트럭 무게 예측

  • Yu-jin, Lee (Department of Business Administration, Pusan National University) ;
  • Kyung Min, Choi (Department of Business Administration, Pusan National University) ;
  • Song-eun, Kim (Department of Business Administration, Pusan National University) ;
  • Kyungsu, Park (Department of Business Administration, Pusan National University) ;
  • Seung Hwan, Jung (School of Business, Yonsei University)
  • Received : 2022.11.28
  • Accepted : 2022.12.12
  • Published : 2022.12.31
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Abstract

Many manufacturers applying third party logistics (3PLs) have some challenges to increase their logistics efficiency. This study introduces an effort to estimate the weight of the delivery trucks provided by 3PL providers, which allows the manufacturer to package and load products in trailers in advance to reduce delivery time. The accuracy of the weigh estimation is more important due to the total weight regulation. This study uses not only the data from the company but also many general prediction variables such as weather, oil prices and population of destinations. In addition, operational statistics variables are developed to indicate the availabilities of the trucks in a specific weight category for each 3PL provider. The prediction model using XGBoost regressor and permutation feature importance method provides highly acceptable performance with MAPE of 2.785% and shows the effectiveness of the developed operational statistics variables.

Keywords

Acknowledgement

This work was supported by Yonsei Business Research Institute and National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) (No. 2022R1C1C101173111).

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