Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains
Abstract In the face of forest fire emergencies, fast and efficient dispatching of rescue vehicles is an important means of mitigating the damage caused by forest fires, and is an effective method of avoiding secondary damage caused by forest fires, minimizing the damage caused by forest fires to th...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-85638-3 |
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| author | Jie Zhang Junnan He Shihao Ren Pei Zhou Jun Guo Mingyue Song |
| author_facet | Jie Zhang Junnan He Shihao Ren Pei Zhou Jun Guo Mingyue Song |
| author_sort | Jie Zhang |
| collection | DOAJ |
| description | Abstract In the face of forest fire emergencies, fast and efficient dispatching of rescue vehicles is an important means of mitigating the damage caused by forest fires, and is an effective method of avoiding secondary damage caused by forest fires, minimizing the damage caused by forest fires to the ecosystem, and mitigating the losses caused by economic development. this paper takes the actual problem as the starting point, constructs a reasonable mathematical model of the problem, for the special characteristics of the emergency rescue vehicle scheduling problem of forest fires, taking into account the actual road conditions in the northern pristine forest area, through the analysis of the cost of paths between the forest area and the highway, to obtain the least obstructed rescue paths, to narrow the gap between the theoretical model and the problem of the actual. Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm’s solution efficiency and accuracy, through the northern pristine forest area of Daxing’anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program. It enriches the solution method of forest fire emergency rescue vehicle dispatching problem in Great Khingan area, which is of great significance to improve the emergency rescue capability in case of sudden forest fire. Through simulation experiments, the proposed Improved Genetic Algorithm (IGA) achieved an average rescue time reduction of 8.5% compared to conventional Genetic Algorithm (GA) and 3.5% compared to Improved Artificial Bee Colony (IABC) algorithm, with an average solution time of 9.4 ms. |
| format | Article |
| id | doaj-art-7662033dbfe44ee5a295c56e93bd607a |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-7662033dbfe44ee5a295c56e93bd607a2025-01-12T12:16:24ZengNature PortfolioScientific Reports2045-23222025-01-0115111510.1038/s41598-025-85638-3Research on vehicle scheduling for forest fires in the northern Greater Khingan MountainsJie Zhang0Junnan He1Shihao Ren2Pei Zhou3Jun Guo4Mingyue Song5College of Energy and Transportation Engineering, Inner Mongolia Agricultural UniversityCollege of Energy and Transportation Engineering, Inner Mongolia Agricultural UniversityCollege of Energy and Transportation Engineering, Inner Mongolia Agricultural UniversityCollege of Forestry, Inner Mongolia Agricultural UniversityCollege of Energy and Transportation Engineering, Inner Mongolia Agricultural UniversityCollege of Energy and Transportation Engineering, Inner Mongolia Agricultural UniversityAbstract In the face of forest fire emergencies, fast and efficient dispatching of rescue vehicles is an important means of mitigating the damage caused by forest fires, and is an effective method of avoiding secondary damage caused by forest fires, minimizing the damage caused by forest fires to the ecosystem, and mitigating the losses caused by economic development. this paper takes the actual problem as the starting point, constructs a reasonable mathematical model of the problem, for the special characteristics of the emergency rescue vehicle scheduling problem of forest fires, taking into account the actual road conditions in the northern pristine forest area, through the analysis of the cost of paths between the forest area and the highway, to obtain the least obstructed rescue paths, to narrow the gap between the theoretical model and the problem of the actual. Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm’s solution efficiency and accuracy, through the northern pristine forest area of Daxing’anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program. It enriches the solution method of forest fire emergency rescue vehicle dispatching problem in Great Khingan area, which is of great significance to improve the emergency rescue capability in case of sudden forest fire. Through simulation experiments, the proposed Improved Genetic Algorithm (IGA) achieved an average rescue time reduction of 8.5% compared to conventional Genetic Algorithm (GA) and 3.5% compared to Improved Artificial Bee Colony (IABC) algorithm, with an average solution time of 9.4 ms.https://doi.org/10.1038/s41598-025-85638-3Emergency reliefImproved genetic algorithmsVehicle schedulingChaos Search |
| spellingShingle | Jie Zhang Junnan He Shihao Ren Pei Zhou Jun Guo Mingyue Song Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains Scientific Reports Emergency relief Improved genetic algorithms Vehicle scheduling Chaos Search |
| title | Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains |
| title_full | Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains |
| title_fullStr | Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains |
| title_full_unstemmed | Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains |
| title_short | Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains |
| title_sort | research on vehicle scheduling for forest fires in the northern greater khingan mountains |
| topic | Emergency relief Improved genetic algorithms Vehicle scheduling Chaos Search |
| url | https://doi.org/10.1038/s41598-025-85638-3 |
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