LAPSE:2023.35924
Published Article

LAPSE:2023.35924
Emergency Material Scheduling Optimization Method Using Multi-Disaster Point Distribution Approach
June 7, 2023
Abstract
The outbreak of multiple disaster sites during the coronavirus disease 2019 (COVID-19) pandemic has presented challenges due to varying access time intensity, population density, and medical resources at each site. To address these issues, this study focuses on 13 districts and counties in Wuhan, China. The importance of each research area is analyzed using the improved PageRank and TOPSIS algorithms to determine the optimal site selection plan. Additionally, a particle swarm algorithm is used to construct an emergency material dispatching model that targets both distribution and site selection costs to solve the multi-distribution center dispatching problem. The results suggest that constructing 10 distribution centers can satisfy the demand for epidemic prevention and control in Wuhan city while saving costs associated with site selection and material distribution. Compared to the previous optimal solution, the distribution and site selection costs under the optimal solution decreased by 27.9% and 17.82%, respectively. This approach can serve as a basis for dispatching emergency materials during public health emergencies.
The outbreak of multiple disaster sites during the coronavirus disease 2019 (COVID-19) pandemic has presented challenges due to varying access time intensity, population density, and medical resources at each site. To address these issues, this study focuses on 13 districts and counties in Wuhan, China. The importance of each research area is analyzed using the improved PageRank and TOPSIS algorithms to determine the optimal site selection plan. Additionally, a particle swarm algorithm is used to construct an emergency material dispatching model that targets both distribution and site selection costs to solve the multi-distribution center dispatching problem. The results suggest that constructing 10 distribution centers can satisfy the demand for epidemic prevention and control in Wuhan city while saving costs associated with site selection and material distribution. Compared to the previous optimal solution, the distribution and site selection costs under the optimal solution decreased by 27.9% and 17.82%, respectively. This approach can serve as a basis for dispatching emergency materials during public health emergencies.
Record ID
Keywords
emergency dispatch, epidemic prevention and control, logistics engineering, multi-distribution center problem, TOPSIS decision
Subject
Suggested Citation
Chang M, Xu H, Hao D, Zhou J, Liu C, Zhong C. Emergency Material Scheduling Optimization Method Using Multi-Disaster Point Distribution Approach. (2023). LAPSE:2023.35924
Author Affiliations
Chang M: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China [ORCID]
Xu H: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Hao D: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Zhou J: School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin 541004, China
Liu C: School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin 541004, China
Zhong C: School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China
Xu H: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Hao D: School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China
Zhou J: School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin 541004, China
Liu C: School of Architecture and Transportation, Guilin University of Electronic Technology, Guilin 541004, China
Zhong C: School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518061, China
Journal Name
Processes
Volume
11
Issue
5
First Page
1330
Year
2023
Publication Date
2023-04-25
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11051330, Publication Type: Journal Article
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Published Article

LAPSE:2023.35924
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https://doi.org/10.3390/pr11051330
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[v1] (Original Submission)
Jun 7, 2023
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Jun 7, 2023
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https://psecommunity.org/LAPSE:2023.35924
Record Owner
Calvin Tsay
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