Disaster spread simulation and rescue time optimization in a resource network

• Published in: Information sciences 2015-03, Vol.298, p.118-135
• Main Authors: Hu, Zhi-Hua, Sheng, Zhao-Han
• Format: Article
• Language: English
• Subjects: Agents (artificial intelligence); Bulk yard; Computer simulation; Construction; Disaster management; Disaster spread; Disasters; Emergency management; Multi-agent system; Networks; Optimization; Simulation; Spreads
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2014.12.011

•Resource network is modeled with structures and behaviors for disaster spread.•Evolution of resource network by disasters is analyzed by simulation.•Evolution of disaster loss, disastrous energy and cost for relief are studied.•Dynamics of rescue times and emergency resource demands are examined.•Decision models for disaster relief are built by analyzing the evolutionary tendency. To design and verify disaster rescue programs in cases of disaster spread, this study presents a base application tool for the simulation, assessment and analysis of disaster spread in a complex resource network based on a multi-agent system (MAS). Various yards, warehouses, distribution centers and other storage nodes are typical resource-intensive sites at which catastrophes and disasters, such as fires and chemical leakage, are prone to occur and spread. Resources are stored in block units called resource nodes. Each resource node is represented by an agent in an MAS. A resource network (network of resource storage nodes) is formed from the disaster spread relationships among resource nodes. Disaster spread simulation and rescue time analysis in resource networks are key problems in disaster prevention and relief. Based on the principles of disaster spread in resource networks, a property model of resource nodes is proposed that incorporates the values of the resources, the disastrous energy of each node, the disaster spread path, and the disaster spread characteristics. To study the dynamics of disaster spread, a state diagram is used to construct a microscopic behavior model for the resource nodes by regarding the resource nodes as agents. Then, decision models are gradually constructed to determine the optimal times for disaster rescue and emergency resource preparation. The proposed models are demonstrated using a multi-layer simulation system.