Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. (August 2017)

• Record Type: Journal Article
• Authors: Islam, Muhammad Saiful; Nepal, Madhav Prasad; Skitmore, Martin; Attarzadeh, Meghdad
• Is Part Of: Advanced engineering informatics. Volume 33(2017)
• Page Start: 112
• Page End: 131
• Publication Date: 2017-08
• Subjects: Construction projects -- Risk assessment -- Fuzzy logic -- Bayesian belief network -- Decision making; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2017.06.001
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: Fuzzy-based methods applied in construction management field are reviewed. The review focuses on basic fuzzy, extended fuzzy and hybrid fuzzy methods. The assessment of complex, interdependent project risks is challenging. Fuzzy Bayesian belief network has broader applications for risk assessment. Abstract: Fuzzy and hybrid methods have been increasingly used in construction risk management research and this study aims to compile and analyse the basic concepts and methods applied in this field to date. A content analysis is made of a comprehensive literature review of publications during 2005–2017. It is found that the nature of complex projects is such that most risks are interdependent of each other. Therefore, a fuzzy structured method such as the fuzzy analytical network process (FANP) has frequently been used for different complex projects. However, the application of FANP is limited because of the tedious and lengthy calculations required for the pairwise comparisons needed and an inability to incorporate new information into the risk structure. To overcome this constraint, a fuzzy Bayesian belief network (FBBN) has been increasingly used for risk assessment. Further project-specific studies based on FBBN are recommended to justify its broader application. Beyond fuzzy methods, the Credal network – an extended form of Bayesian network- is found to have potential for risk assessment under uncertainty.