Project risk assessment model combining the fuzzy weighted average principle with a similarity measure

Pejman Rezakhani, Won Suk Jang, Sangwook Lee, Dong Eun Lee

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This paper presents a fuzzy risk assessment model for construction projects. The model combines the fuzzy weighted average principle with a similarity measure of generalized fuzzy numbers. The failure probability of each project objective can be evaluated using a discrete fuzzy weighted average algorithm and translated into an appropriate fuzzy linguistic term by using a modified similarity measure determined by considering the area, perimeter, height, and geometric distance of generalized fuzzy numbers. This paper makes practical contributions by suggesting a model that can address the uncertainty associated with construction projects based on fuzzy set theory and facilitate the assessment of fuzzy risks by allowing for sophisticated computations and theoretical contributions by enabling researchers to expeditiously assess project risks. A test case verifies the usability and validity of the proposed method.

Original languageEnglish
Pages (from-to)521-530
Number of pages10
JournalKSCE Journal of Civil Engineering
Volume18
Issue number2
DOIs
StatePublished - Mar 2014

Keywords

  • fuzzy risk assessment
  • fuzzy weighted average
  • generalized fuzzy numbers
  • linguistic values
  • similarity measure

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