Intelligent decision system of emergency response based on multi-Agent cooperation in chemical industry park

被引:0
作者
Chen P. [1 ,2 ]
Chen G. [1 ,2 ]
Zhou L. [1 ,2 ]
Men J. [1 ,2 ]
机构
[1] Institute of Safety Science & Engineering, South China University of Technology, Guangzhou
[2] Guangdong Provincial Science and Technology Collaborative Innovation Center for Work Safety, Guangzhou
来源
Huagong Jinzhan/Chemical Industry and Engineering Progress | 2021年 / 40卷 / 08期
关键词
Chemical industrial park; Emergency response; Model; Multi-Agent collaborative emergency decision; Safety; Systems engineering;
D O I
10.16085/j.issn.1000-6613.2020-1845
中图分类号
学科分类号
摘要
The emergency response of the chemical industry park (CIP) has the spatial-temporal characteristics of dynamic and hierarchical emergency decision-making, conflict and synergy of the emergency rescue (ER), and the emergency evacuation (EE). In different emergency response stages, the road network of the CIP is in the state of synchronous heterogeneous activities, such as the ER Agent and the EE Agent. Therefore, a new method of route planning considers separate emergency response stages, is proposed in this study. Firstly, the four levels of emergency response are enhanced, and a hybrid intelligent decision-making system framework is proposed. Secondly, the temporal and spatial variation of multi-Agent emergency decision-making in the CIP is analyzed, and the multi-Agent intelligent decision-making models are established, respectively, for the emergency response stage inside the enterprises, the emergency response stage inside the CIP, and the collaborative emergency response stage both inside and outside the CIP. Finally, based on the hybrid MAS system and collaboration theory, the multi-agent information-sharing relationship and cooperation model based on three-tier emergency intelligent decision-making model in the CIP were constructed. The intelligent decision-making system for the whole process of emergency response can provide important theoretical basis and technical support for the emergency decision-making in the CIP. © 2021, Chemical Industry Press Co., Ltd. All right reserved.
引用
收藏
页码:4656 / 4665
页数:9
相关论文
共 28 条
[1]  
ZHANG Xinmei, CHEN Guohua, ZHANG Hui, Et al., Study on shortcomings of emergency management system in China and its development countermeasures, China Safety Science Journal, 16, 2, pp. 79-84, (2006)
[2]  
OTHMAN S, BEYDOUN G., Model-driven disaster management, Information & Management, 50, 5, pp. 218-228, (2013)
[3]  
DUAN Zaipeng, QIAN Xinming, XIA Dengyou, Emergency resources demand forecast based on FCM and CBR-GRA dual search, Journal of Northeastern University Natural Science, 37, 5, pp. 756-760, (2016)
[4]  
Jinkun MEN, JIANG Peng, XU Huan, A chance constrained programming approach for HazMat capacitated vehicle routing problem in Type-2 fuzzy environment, Journal of Cleaner Production, 237, 10, (2019)
[5]  
WEI Jinyin, GUO Qi, SHI Bin, Et al., Route optimizing on secondary distribution of refined oil considering time-dependent risk, Chemical Industry and Engineering Progress, 39, 4, pp. 1597-1604, (2020)
[6]  
COVA T, JOHNSON J P., Microsimulation of neighborhood evacuations in the urban-wildland interface, Environment & Planning A, 34, 12, pp. 2211-2229, (2002)
[7]  
SARWAR M, ANASTASOPOULOS P C, UKKUSURI S V, Et al., A statistical analysis of the dynamics of household hurricane-evacuation decisions, Transportation, 45, 1, pp. 51-70, (2018)
[8]  
ZENG Yiping, SONG Weiguo, HUO Feizhou, Et al., Modeling evacuation dynamics on stairs by an extended optimal steps model, Simulation Modelling Practice and Theory, 84, pp. 177-189, (2018)
[9]  
LI Jia, WANG Jinghong, JIN Bowei, Et al., Evacuation of nursing home based on massmotion: effect of the distribution of dependent elderly, KSCE Journal of Civil Engineering, 24, 4, pp. 1330-1337, (2020)
[10]  
ZHAO Ming, CHEN Qiuwen, Risk-based optimization of emergency rescue facilities locations for large-scale environmental accidents to improve urban public safety, Natural Hazards, 75, 1, pp. 163-189, (2015)