Integrating system dynamics and fuzzy logic modelling for construction risk management

F. Nasirzadeh, A. Afshar, M. Khanzadi, S.M. Howick

Research output: Contribution to journalArticle

50 Citations (Scopus)

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.
LanguageEnglish
Pages1197-1212
Number of pages15
JournalConstruction Management and Economics
Volume26
Issue number11
DOIs
Publication statusPublished - Nov 2008

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Risk management
Fuzzy logic
Dynamical systems
Modeling
System dynamics
Risk analysis
Project management
Life cycle
Computer simulation

Keywords

  • system dynamics
  • fuzzy logic
  • fuzzy logic modelling
  • construction risk management
  • risk

Cite this

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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.",
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Integrating system dynamics and fuzzy logic modelling for construction risk management. / Nasirzadeh, F.; Afshar, A.; Khanzadi, M.; Howick, S.M.

In: Construction Management and Economics, Vol. 26, No. 11, 11.2008, p. 1197-1212.

Research output: Contribution to journalArticle

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