Fuzzy inference to risk assessment on nuclear engineering systems
Applied Soft Computing
Fuzzy hierarchical TOPSIS for supplier selection
Applied Soft Computing
A fuzzy AHP approach to personnel selection problem
Applied Soft Computing
Application of a Fuzzy AHP Method to Risk Assessment of International Construction Projects
ECBI '09 Proceedings of the 2009 International Conference on Electronic Commerce and Business Intelligence
Fuzzy MCDM approach for selecting the best environment-watershed plan
Applied Soft Computing
A combined methodology for supplier selection and performance evaluation
Expert Systems with Applications: An International Journal
Estimating the quality of process yield by fuzzy sets and systems
Expert Systems with Applications: An International Journal
Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP
Expert Systems with Applications: An International Journal
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Construction projects are initiated in dynamic environment which result in circumstances of high uncertainty and risks due to accumulation of many interrelated parameters. The purpose of this study is to use novel analytic tools to evaluate the construction projects and their overall risks under incomplete and uncertain situations. It was also aimed to place the risk in a proper category and predict the level of it in advance to develop strategies and counteract the high-risk factors. The study covers identifying the key risk criteria of construction projects at King Abdulaziz University (KAU), and assessing the criteria by the integrated hybrid methodologies. The proposed hybrid methodologies were initiated with a survey for data collection. The relative importance index (RII) method was applied to prioritize the project risks based on the data obtained. The construction projects were then categorized by fuzzy AHP and fuzzy TOPSIS methodologies. Fuzzy AHP (FAHP) was used to create favorable weights for fuzzy linguistic variable of construction projects overall risk. The fuzzy TOPSIS method is very suitable for solving group decision making problems under the fuzzy environment. It attempted to incorporate vital qualitative attributes in performance analysis of construction projects and transformed the qualitative data into equivalent quantitative measures. Thirty construction projects were studied with respect to five main criteria that are the time, cost, quality, safety and environment sustainability. The results showed that these novel methodologies are able to assess the overall risks of construction projects, select the project that has the lowest risk with the contribution of relative importance index. This approach will have potential applications in the future.