Optimization of emergency logistics for urban flooding with consideration of rainfall effects
Abstract Urban flooding frequently causes significant damage to infrastructure and facilities, leading to critical supply shortages in affected regions. Ensuring rapid and efficient distribution of relief supplies remains a key challenge during disaster response operations. This study proposes a two...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-09986-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849226261713387520 |
|---|---|
| author | Peiwen Zhang Chenxing Zhang Pan Zhang Xuxian Yan Huawei Yang |
| author_facet | Peiwen Zhang Chenxing Zhang Pan Zhang Xuxian Yan Huawei Yang |
| author_sort | Peiwen Zhang |
| collection | DOAJ |
| description | Abstract Urban flooding frequently causes significant damage to infrastructure and facilities, leading to critical supply shortages in affected regions. Ensuring rapid and efficient distribution of relief supplies remains a key challenge during disaster response operations. This study proposes a two-stage optimization framework for emergency logistics. First, a supply distribution model is developed by integrating resource scarcity indices and disaster severity indices, optimized through a simulated annealing algorithm. Second, a vehicle routing model accounting for rainfall and dynamic vehicle speeds is established, solved using a hybrid Genetic Simulated Annealing algorithm to enhance computational efficiency. Ultimately, through simulation with randomly generated calculation examples, it was found that for the supply distribution model, the allocation model that takes into account both the resource scarcity index and the disaster index is more suitable for scenarios with an uneven distribution of disaster severity. The results of the model that takes into account the resource scarcity index, disaster index and waiting time index shows an improvement of 4% over the model that doesn’t consider the resource scarcity index. The experimental results show that the proposed methodology not only adapts to varying disaster spatial patterns but also balances efficiency and equity under supply constraints, offering a scalable tool for designing resilient urban flood response systems. |
| format | Article |
| id | doaj-art-2f4f794f69d348858e81bc1ded918630 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-2f4f794f69d348858e81bc1ded9186302025-08-24T11:29:05ZengNature PortfolioScientific Reports2045-23222025-08-0115111510.1038/s41598-025-09986-wOptimization of emergency logistics for urban flooding with consideration of rainfall effectsPeiwen Zhang0Chenxing Zhang1Pan Zhang2Xuxian Yan3Huawei Yang4School of Management Science and Engineering, Shanxi University of Finance and EconomicsSchool of Management Science and Engineering, Shanxi University of Finance and EconomicsSchool of Management Science and Engineering, Shanxi University of Finance and EconomicsSchool of Management Science and Engineering, Shanxi University of Finance and EconomicsSchool of Management Science and Engineering, Shanxi University of Finance and EconomicsAbstract Urban flooding frequently causes significant damage to infrastructure and facilities, leading to critical supply shortages in affected regions. Ensuring rapid and efficient distribution of relief supplies remains a key challenge during disaster response operations. This study proposes a two-stage optimization framework for emergency logistics. First, a supply distribution model is developed by integrating resource scarcity indices and disaster severity indices, optimized through a simulated annealing algorithm. Second, a vehicle routing model accounting for rainfall and dynamic vehicle speeds is established, solved using a hybrid Genetic Simulated Annealing algorithm to enhance computational efficiency. Ultimately, through simulation with randomly generated calculation examples, it was found that for the supply distribution model, the allocation model that takes into account both the resource scarcity index and the disaster index is more suitable for scenarios with an uneven distribution of disaster severity. The results of the model that takes into account the resource scarcity index, disaster index and waiting time index shows an improvement of 4% over the model that doesn’t consider the resource scarcity index. The experimental results show that the proposed methodology not only adapts to varying disaster spatial patterns but also balances efficiency and equity under supply constraints, offering a scalable tool for designing resilient urban flood response systems.https://doi.org/10.1038/s41598-025-09986-wEmergency logisticsVictim satisfactionUrban floodVehicle routing optimization |
| spellingShingle | Peiwen Zhang Chenxing Zhang Pan Zhang Xuxian Yan Huawei Yang Optimization of emergency logistics for urban flooding with consideration of rainfall effects Scientific Reports Emergency logistics Victim satisfaction Urban flood Vehicle routing optimization |
| title | Optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| title_full | Optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| title_fullStr | Optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| title_full_unstemmed | Optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| title_short | Optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| title_sort | optimization of emergency logistics for urban flooding with consideration of rainfall effects |
| topic | Emergency logistics Victim satisfaction Urban flood Vehicle routing optimization |
| url | https://doi.org/10.1038/s41598-025-09986-w |
| work_keys_str_mv | AT peiwenzhang optimizationofemergencylogisticsforurbanfloodingwithconsiderationofrainfalleffects AT chenxingzhang optimizationofemergencylogisticsforurbanfloodingwithconsiderationofrainfalleffects AT panzhang optimizationofemergencylogisticsforurbanfloodingwithconsiderationofrainfalleffects AT xuxianyan optimizationofemergencylogisticsforurbanfloodingwithconsiderationofrainfalleffects AT huaweiyang optimizationofemergencylogisticsforurbanfloodingwithconsiderationofrainfalleffects |