Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow

作     者：Zhiming Ding Zilin Zhao Detian Liu Yang Cao 

作者机构：Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Institute of SoftwareChinese Academy of ScienceBeijing 100190China School of InformationBeijing Wuzi UniversityBeijing 101149China 

出 版 物：《Journal of Safety Science and Resilience》 (安全科学与韧性（英文）)

年 卷 期：2021年第2卷第4期

页      面：222-229页

核心收录：

学科分类：08[工学] 081203[工学-计算机应用技术] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Key R&D Program of China(No.2017YFC0803300) the National Natural Science of Foundation of China(No.91646201) the General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China(No.KM202110037002) the Youth Fund Project of Beijing Wuzi University(No.2020XJQN02) Research Project Plan of China Society of Logistics and China Federation of Logistics and Purchasing(No.2021CSLKT3-247). 

主　　题：Logistics scheduling MOP Swarm intelligence algorithms Spatio-temporal trajectory Traffic flow 

摘      要：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’satisfac-tion 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.