Interval Grey Fuzzy Uncertain Linguistic Sets and Their Application to Ranking of Construction Project Risk Factors

Abstract

To express information on construction project risks comprehensively and precisely and to improve the accuracy of the results of the ranking of construction project risk factors, we use the interval grey degree to express grey characteristics of information. The membership degree is used to express fuzzy characteristics of information. An uncertain linguistic variable is used to express linguistic descriptive characteristics of information. A ranking model for construction project risk factors is proposed to identify the main risk factors on the basis of the interval grey fuzzy uncertain linguistic set and the continuous interval argument ordered weighted averaging (C-OWA) operator. We take the Weft Three-Road Cross-River Tunnel in Nanjing as a case to verify the feasibility of the proposed model. Research results show that compared with fuzzy sets that can only use membership degree to express fuzziness, the interval grey fuzzy uncertain linguistic set can express the grey, fuzzy, and linguistic descriptive characteristics of practical construction project risk information simultaneously. The proposed model based on the theory helps to improve the comprehensiveness and authenticity of risk information expression, as well as the accuracy of risk factor rankings. The results of this work could assist project managers in determining main risk factors and thereby provide a theoretical basis for taking pre-control measures.