Author(s)

Yuliang Dong ¹

Affiliation(s)

¹ School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China

Corresponding Author

Yuliang Dong

ABSTRACT

The first part of this paper is based on the logistics network line freight data, and the ARIMA time series prediction model is used to predict the cargo transportation situation of each logistics point and the corresponding logistics routes in 2023-01-01 to 2023-01-31. Then, according to the paper requirement, the prediction results of DC14 DC10, DC20 DC35, DC 65 and DC25 at 95% confidence interval. Meanwhile, based on the model one results, this paper gives the residual analysis and the covariance analysis, so as to analyze the robustness of the results. In the second part, due to the closure of DC5 in the logistics site, the cargo quantity of DC5 needs to be allocated. Considering the difference between the access volume and the shipment quantity of DC5 site, this paper analyzes the entry and output respectively. First, based on model 1, the paper predicts the amount of goods to be processed at the DC5 site. Then, based on the constraints, This is transformed into a multi-objective linear planning, and finally based on the model, the DC5 cargo allocation arrangement under the normal operation of the logistics transportation network and the logistics network load are obtained. In this paper, a 0/1 integer planning model is established to deal with the cargo distribution of DC9 shutdown, and introduce decision variables to determine the opening and closing state of a line. Then, based on the model one, the quantity of goods that DC9 site should be processed is predicted, and these goods are allocated to some existing lines and newly opened lines. Meanwhile, in order to save management costs, some lines with low cargo load are shut down, and then the logistics and transportation network is optimized.

KEYWORDS

ARIMA; Multi-objective Linear Planning; 0/1 Integer Programming

CITE THIS PAPER

Yuliang Dong, Research on the transportation and structure optimization of logistics network parcels. Industrial Engineering and Innovation Management (2023) Vol. 6: 104-113. DOI: http://dx.doi.org/10.23977/ieim.2023.061014.

REFERENCES

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