Logistics transportation model based on ARIMA and linear programming

With the popularization of the Internet, the e-commerce logistics network has seen rapid growth. However, factors such as holidays, epidemics, and natural disasters like earthquakes can cause fluctuations in order volumes from e-commerce users, leading to changes in parcel quantities at each logistics site. To ensure the smooth operation of the logistics network, this paper conducts an in-depth analysis of the circulation relationships between different routes and establishes an ARIMA model and linear programming model. By utilizing existing data, this article study various scenarios that may occur at logistics sites. Based on these models, this article obtain line prediction results using the available data and construct a line adjustment model in a dynamic environment. This model effectively addresses sudden situations, enhancing the flexibility and responsiveness of the logistics system, thereby optimizing the operational efficiency and service quality of the entire logistics network. It provides robust support for the development of e-commerce logistics.

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Publication Details

Journal
Highlights in Business Economics and Management
Published
2025-03-17
DOI
https://doi.org/10.54097/wr3ny989
Primary Topic
Simulation and Modeling Applications
Type
article
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article

Logistics transportation model based on ARIMA and linear programming

Xiaotian Zhu, S. Chen
Highlights in Business Economics and Management
Simulation and Modeling Applications
article

Logistics transportation model based on ARIMA and linear programming

Xiaotian Zhu, S. Chen
article en

Abstract

With the popularization of the Internet, the e-commerce logistics network has seen rapid growth. However, factors such as holidays, epidemics, and natural disasters like earthquakes can cause fluctuations in order volumes from e-commerce users, leading to changes in parcel quantities at each logistics site. To ensure the smooth operation of the logistics network, this paper conducts an in-depth analysis of the circulation relationships between different routes and establishes an ARIMA model and linear programming model. By utilizing existing data, this article study various scenarios that may occur at logistics sites. Based on these models, this article obtain line prediction results using the available data and construct a line adjustment model in a dynamic environment. This model effectively addresses sudden situations, enhancing the flexibility and responsiveness of the logistics system, thereby optimizing the operational efficiency and service quality of the entire logistics network. It provides robust support for the development of e-commerce logistics.

Highlights in Business Economics and ManagementVol. 53
Jimei University (CN)
Openalex Percentile: Top 92%
Simulation and Modeling Applications
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