Optimizing multi-vehicle emergency perishable material distribution across multiple centers with a freshness consideration

Optimizing the distribution of perishable emergency materials in the aftermath of sudden disasters holds significant theoretical and practical value. This paper begins by defining the freshness of perishable emergency materials and develops a continuous piecewise function to describe the changes in quality and quantity of these materials at different time stages. Additionally, it considers distinct delivery requirements for each demand point regarding the same perishable emergency materials. Under the minimum freshness constraint, a vehicle distribution optimization model is established for perishable emergency materials, considering multiple distribution centers and multiple vehicles. Depending on whether the distribution center has an adequate number of vehicles, the solution can be classified into three scenarios. In the case of insufficient total emergency supplies but sufficient vehicles, an accurate algorithm is designed to address the model. Alternatively, when both the total emergency supplies and vehicles are insufficient, an approximate algorithm is developed to solve the model. Finally, when the total quantity of perishable emergency materials is inadequate, and some vehicles are sufficient while others are not, the problem is transformed into one of the first two situations to find a solution. To validate the accuracy of the model and the effectiveness of the algorithm, an analysis is conducted using the flood-stricken area in Shouguang, Shandong as a case study.

Authors

Publication Details

Journal
International Journal of Industrial Engineering Computations
Published
2025-01-01
DOI
https://doi.org/10.5267/j.ijiec.2025.8.009
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
1.24
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article

Optimizing multi-vehicle emergency perishable material distribution across multiple centers with a freshness consideration

Zichun Zhang, Xu Yang, Xiaodong Li, Huimin Zhu et al.
1 citations
International Journal of Industrial Engineering Computations
Advanced Manufacturing and Logistics Optimization
1.24
article

Optimizing multi-vehicle emergency perishable material distribution across multiple centers with a freshness consideration

Zichun Zhang, Xu Yang, Xiaodong Li, Huimin Zhu, Bing Su
article en
1 citations

Abstract

Optimizing the distribution of perishable emergency materials in the aftermath of sudden disasters holds significant theoretical and practical value. This paper begins by defining the freshness of perishable emergency materials and develops a continuous piecewise function to describe the changes in quality and quantity of these materials at different time stages. Additionally, it considers distinct delivery requirements for each demand point regarding the same perishable emergency materials. Under the minimum freshness constraint, a vehicle distribution optimization model is established for perishable emergency materials, considering multiple distribution centers and multiple vehicles. Depending on whether the distribution center has an adequate number of vehicles, the solution can be classified into three scenarios. In the case of insufficient total emergency supplies but sufficient vehicles, an accurate algorithm is designed to address the model. Alternatively, when both the total emergency supplies and vehicles are insufficient, an approximate algorithm is developed to solve the model. Finally, when the total quantity of perishable emergency materials is inadequate, and some vehicles are sufficient while others are not, the problem is transformed into one of the first two situations to find a solution. To validate the accuracy of the model and the effectiveness of the algorithm, an analysis is conducted using the flood-stricken area in Shouguang, Shandong as a case study.

International Journal of Industrial Engineering ComputationsVol. 16(4)
Openalex Percentile: Top 16%
Advanced Manufacturing and Logistics Optimization
1.24
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