Emergency logistics scheduling with multiple supply-demand points based on grey interval
This study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points. In large-scale natural disasters, it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2022-06-01
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| Series: | Journal of Safety Science and Resilience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666449622000019 |
| _version_ | 1818113358813986816 |
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| author | Zhiming Ding Xinrun Xu Shan Jiang Jin Yan Yanbo Han |
| author_facet | Zhiming Ding Xinrun Xu Shan Jiang Jin Yan Yanbo Han |
| author_sort | Zhiming Ding |
| collection | DOAJ |
| description | This study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points. In large-scale natural disasters, it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster sites and to determine emergency material scheduling solutions accurately. Furthermore, the quantity of emergency materials required at each disaster site is uncertain. To address this issue, in this study, we developed an emergency material scheduling model with multiple logistics supply points for multiple demand points based on the grey interval numbers. To optimize the proposed multi-supply-point and multi-demand-point emergency material scheduling mode, a multi-objective optimization algorithm based on a genetic algorithm was used. Experimental results demonstrate that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm optimization multi-objective solution algorithm. Additionally, the multi-supply point and multi-demand point emergency material dispatch model and optimization algorithm provides robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities. |
| first_indexed | 2024-12-11T03:33:34Z |
| format | Article |
| id | doaj.art-6958d1fe03704b738a0e599e407d90e4 |
| institution | Directory Open Access Journal |
| issn | 2666-4496 |
| language | English |
| last_indexed | 2024-12-11T03:33:34Z |
| publishDate | 2022-06-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Safety Science and Resilience |
| spelling | doaj.art-6958d1fe03704b738a0e599e407d90e42022-12-22T01:22:19ZengKeAi Communications Co., Ltd.Journal of Safety Science and Resilience2666-44962022-06-0132179188Emergency logistics scheduling with multiple supply-demand points based on grey intervalZhiming Ding0Xinrun Xu1Shan Jiang2Jin Yan3Yanbo Han4Institute of Software Chinese Academy of Sciences, Beijing, 050052, China; Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, Beijing, 100124，ChinaUniversity of Chinese Academy of Sciences, Beijing, 100049, China; Institute of Software Chinese Academy of Sciences, Beijing, 050052, ChinaCorresponding author.; University of Chinese Academy of Sciences, Beijing, 100049, China; Institute of Software Chinese Academy of Sciences, Beijing, 050052, ChinaUniversity of Chinese Academy of Sciences, Beijing, 100049, China; Institute of Software Chinese Academy of Sciences, Beijing, 050052, ChinaBeijing Key Laboratory on Integration and Analysis of Large-scale Stream Data, Beijing, 100124，China; North China University of Technology, Beijing, 100144，ChinaThis study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points. In large-scale natural disasters, it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster sites and to determine emergency material scheduling solutions accurately. Furthermore, the quantity of emergency materials required at each disaster site is uncertain. To address this issue, in this study, we developed an emergency material scheduling model with multiple logistics supply points for multiple demand points based on the grey interval numbers. To optimize the proposed multi-supply-point and multi-demand-point emergency material scheduling mode, a multi-objective optimization algorithm based on a genetic algorithm was used. Experimental results demonstrate that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm optimization multi-objective solution algorithm. Additionally, the multi-supply point and multi-demand point emergency material dispatch model and optimization algorithm provides robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities.http://www.sciencedirect.com/science/article/pii/S2666449622000019Emergency logistics schedulingMulti-objective programmingDisaster relief |
| spellingShingle | Zhiming Ding Xinrun Xu Shan Jiang Jin Yan Yanbo Han Emergency logistics scheduling with multiple supply-demand points based on grey interval Journal of Safety Science and Resilience Emergency logistics scheduling Multi-objective programming Disaster relief |
| title | Emergency logistics scheduling with multiple supply-demand points based on grey interval |
| title_full | Emergency logistics scheduling with multiple supply-demand points based on grey interval |
| title_fullStr | Emergency logistics scheduling with multiple supply-demand points based on grey interval |
| title_full_unstemmed | Emergency logistics scheduling with multiple supply-demand points based on grey interval |
| title_short | Emergency logistics scheduling with multiple supply-demand points based on grey interval |
| title_sort | emergency logistics scheduling with multiple supply demand points based on grey interval |
| topic | Emergency logistics scheduling Multi-objective programming Disaster relief |
| url | http://www.sciencedirect.com/science/article/pii/S2666449622000019 |
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