Agent-based modeling and simulation to assess flood preparedness and recovery of manufacturing small and medium-sized enterprises. (February 2019)

• Record Type: Journal Article
• Authors: Coates, Graham; Li, Chunhui; Ahilan, Sangaralingam; Wright, Nigel; Alharbi, Meshal
• Is Part Of: Engineering applications of artificial intelligence. Volume 78(2019)
• Page Start: 195
• Page End: 217
• Publication Date: 2019-02
• Subjects: Agent-based modeling/simulation -- Flood preparedness/recovery -- SMEs; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2018.11.010
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Severe flooding has caused major damage and disruption to households, communities, businesses, and organizations in many parts of the world. In the United Kingdom (UK), flooding has been responsible for significant losses to the economy due to its impact on businesses, 99.9% of which are Small and Medium-sized Enterprises (SMEs). This paper reports on how agent-based modeling and simulation has been developed and used to assess the effectiveness of a range of physical/structural and social preparedness adaptation measures that can be implemented by manufacturing SMEs to reduce the impact of and expedite recovery from a major flood event. Results indicate the effectiveness of combinations of these adaptation measures in relation to a one in 1000 year flood event that has been modeled and simulated in a key industrial area of the UK which, in addition to having experienced severe flooding, has a high concentration of SMEs. Highlights: Agent based approach to assess flood preparedness measures on SMEs' recovery from flooding. Over 100 semi-structured interviews used to develop agents representing manufacturing SMEs. A one in 1000 year flood event modeled and simulated to enable SMEs affected to be identified. Physical measures more effective than social measures in reducing damage and disruption to SMEs.