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- W4385695005 abstract "This paper explores how to reduce costs and improve efficiency by predicting the package volume at various logistics sites and railways, and arranging transportation and sorting plans in advance. We have established prediction models, optimization models, evaluation models, and conducted in-depth research on emergency transportation and network optimization. The main work of this paper is divided into four aspects. Firstly, data cleaning and prediction using ARIMA and LSTM models; secondly, constructing a cargo distribution optimization model based on the DC5 diversion ratio and solving it using simulated annealing algorithm; thirdly, constructing a flow plan planning model based on three-objective dynamic decision-making and solving it using simulated annealing algorithm. Fourthly, the indicators for evaluating the impact of routes include the number of transported packages, transportation frequency, maximum transportation volume, and transportation balance; for site influence factors, we choose the total amount of goods sent and the number of goods received by the site. We have built a comprehensive evaluation model for site routes based on entropy weight Topsis and conducted five comparative experiments to verify the robustness of the model." @default.
- W4385695005 created "2023-08-10" @default.
- W4385695005 creator A5048086503 @default.
- W4385695005 date "2023-06-16" @default.
- W4385695005 modified "2023-09-25" @default.
- W4385695005 title "Research on Emergency Transportation and Structural Optimization of E-commerce Logistics Network for Goods Volume Prediction and Optimal Scheduling" @default.
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- W4385695005 doi "https://doi.org/10.1109/icaisc58445.2023.10200711" @default.
- W4385695005 hasPublicationYear "2023" @default.
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