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The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

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Integrating system dynamics and fuzzy logic modelling for construction risk management

Nasirzadeh, F. and Afshar, A. and Khanzadi, M. and Howick, S.M. (2008) Integrating system dynamics and fuzzy logic modelling for construction risk management. Construction Management and Economics, 26 (11). pp. 1197-1212. ISSN 0144-6193

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Abstract

The complex structure of construction project risks arises from their internal and external interactions with their dynamic nature throughout the life cycle of the project. A system dynamics (SD) approach to construction project risk management is presented, including risk analysis and response process. Owing to the imprecise and uncertain nature of risks, fuzzy logic is integrated into system dynamics modelling structure. Risk magnitudes are defined by a fuzzy logic based risk magnitude prediction system. Zadeh's extension principle and interval arithmetic is employed in the SD simulation model to present the system outcomes considering uncertainties in the magnitude of risks resulting from the risk magnitude prediction system. The performance of the proposed method is assessed by employing the method in the risk management plan of a sample project. The impact of a sample risk is quantified and efficiency of different alternative response scenarios is assessed. The proposed approach supports different stages of the risk management process considering both the systemic and uncertain nature of risks.