Optimisation study of express delivery quantity prediction based on ARIMA model and grid search algorithm

Jiawei Wang; Yue Gu

doi:10.1117/12.3030634

16 May 2024 Optimisation study of express delivery quantity prediction based on ARIMA model and grid search algorithm

Jiawei Wang, Yue Gu

Proceedings Volume 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024); 131600T (2024) https://doi.org/10.1117/12.3030634
Event: 4th International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 2024, Beijin, China

Abstract

The traditional logistics model is difficult to adapt to personalised and frequent express demand, and urban development and road network restrictions increase the difficulty of path planning and cost control. This study is dedicated to optimising logistics transport, proposing intelligent path planning and dynamic demand forecasting. By accurately predicting the number of urban express delivery, resources are deployed in advance to avoid insufficient or excess capacity and improve the quality of express delivery service. Finding the optimal cost solution under path constraints improves logistics efficiency and achieves more economical and sustainable logistics transport. Apply ARIMA model combined with grid search algorithm to forecast the number of express delivery with actual data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiawei Wang and Yue Gu "Optimisation study of express delivery quantity prediction based on ARIMA model and grid search algorithm", Proc. SPIE 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 131600T (16 May 2024); https://doi.org/10.1117/12.3030634

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KEYWORDS

Autoregressive models

Data modeling

Algorithm development

Autocorrelation

Mathematical optimization

Evolutionary algorithms

Particle swarm optimization

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