Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow
Emergency supplies scheduling needs to consider the state of the demanders, and reasonably scheduling and resource allocation are the heart of efficient rescue. Taking rescue time, scheduling cost and demanders’ satisfaction as goals, in this paper, an emergency supplies scheduling model based on mu...
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KeAi Communications Co., Ltd.
2021
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oai:doaj.org-article:a3f4fc8a676b47e0a674181752a2c9bd2021-11-04T04:40:16ZMulti-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow2666-449610.1016/j.jnlssr.2021.07.003https://doaj.org/article/a3f4fc8a676b47e0a674181752a2c9bd2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666449621000281https://doaj.org/toc/2666-4496Emergency supplies scheduling needs to consider the state of the demanders, and reasonably scheduling and resource allocation are the heart of efficient rescue. Taking rescue time, scheduling cost and demanders’ satisfaction as goals, in this paper, an emergency supplies scheduling model based on multi-objective optimization was proposed to provide a wealth of decision-making information. Then four multi-objective optimization algorithms are employed to obtain the optimal set of scheduling models. In addition, we design the minimum time cost model and the shortest route cost model by considering the change of the road network status. The extensive simulation experiments are conducted on a real urban traffic dataset. The experimental results show that the two cost models can serve different scheduling needs and provide efficient scheduling for emergency supplies.Zhiming DingZilin ZhaoDetian LiuYang CaoKeAi Communications Co., Ltd.articleLogistics schedulingMOPSwarm intelligence algorithmsSpatio-temporal trajectoryTraffic flowRisk in industry. Risk managementHD61ENJournal of Safety Science and Resilience, Vol 2, Iss 4, Pp 222-229 (2021) |
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DOAJ |
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DOAJ |
| language |
EN |
| topic |
Logistics scheduling MOP Swarm intelligence algorithms Spatio-temporal trajectory Traffic flow Risk in industry. Risk management HD61 |
| spellingShingle |
Logistics scheduling MOP Swarm intelligence algorithms Spatio-temporal trajectory Traffic flow Risk in industry. Risk management HD61 Zhiming Ding Zilin Zhao Detian Liu Yang Cao Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| description |
Emergency supplies scheduling needs to consider the state of the demanders, and reasonably scheduling and resource allocation are the heart of efficient rescue. Taking rescue time, scheduling cost and demanders’ satisfaction as goals, in this paper, an emergency supplies scheduling model based on multi-objective optimization was proposed to provide a wealth of decision-making information. Then four multi-objective optimization algorithms are employed to obtain the optimal set of scheduling models. In addition, we design the minimum time cost model and the shortest route cost model by considering the change of the road network status. The extensive simulation experiments are conducted on a real urban traffic dataset. The experimental results show that the two cost models can serve different scheduling needs and provide efficient scheduling for emergency supplies. |
| format |
article |
| author |
Zhiming Ding Zilin Zhao Detian Liu Yang Cao |
| author_facet |
Zhiming Ding Zilin Zhao Detian Liu Yang Cao |
| author_sort |
Zhiming Ding |
| title |
Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| title_short |
Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| title_full |
Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| title_fullStr |
Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| title_full_unstemmed |
Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| title_sort |
multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow |
| publisher |
KeAi Communications Co., Ltd. |
| publishDate |
2021 |
| url |
https://doaj.org/article/a3f4fc8a676b47e0a674181752a2c9bd |
| work_keys_str_mv |
AT zhimingding multiobjectiveschedulingofrelieflogisticsbasedonswarmintelligencealgorithmsandspatiotemporaltrafficflow AT zilinzhao multiobjectiveschedulingofrelieflogisticsbasedonswarmintelligencealgorithmsandspatiotemporaltrafficflow AT detianliu multiobjectiveschedulingofrelieflogisticsbasedonswarmintelligencealgorithmsandspatiotemporaltrafficflow AT yangcao multiobjectiveschedulingofrelieflogisticsbasedonswarmintelligencealgorithmsandspatiotemporaltrafficflow |
| _version_ |
1718445230521319424 |