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Article type: Research Article
Authors: Zolfaghari, S. | Mousavi, S. Meysam; *
Affiliations: Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
Correspondence: [*] Corresponding author. S.M. Mousavi. Tel.: +98 21 51212091; E-mail: [email protected].
Abstract: Project risk management is an essential activity that refers to identify and analyze potential risks to take precautionary responses to mitigate their negative impacts or intensify their positive effects. This study presents a novel approach of failure mode and effect analysis (FMEA) by the aim of prioritizing construction project risks under uncertain conditions of projects. The examined data are defined in the form of a new extension of fuzzy sets, namely hesitant fuzzy sets (HFSs), to involve more possible memberships for evaluation risks’ characteristics. Then, the application of H-VIKOR, VIKOR under hesitant information, and H-Shapley VIKOR is demonstrated to determine ranking order of construction-project risks. A new version of H-Shapley VIKOR method is presented in this study by defining a new evaluation index for ranking alternatives. Moreover, using different multi-attributes decision-making (MADM) methods may lead to several ranking orders. Rank reversal makes problem in complex decision-making process of the construction projects. To solve this problem, a new extension of De-Novo multi-approaches multi-attributes analysis by a group of experts or decision makers (DMs) is introduced to determine precise final ranking order. The extended method is encompassed the preference of project DMs about using different MADM methods. The application and performance of the proposed new FMEA model-based hesitant fuzzy De-Novo multi-approaches-multiple attributes analysis are evaluated through a real case study of highway project risks. The results indicate the efficiency of the proposed FMEA model.
Keywords: Construction-project risk assessment, hesitant fuzzy sets, H-Shapley VIKOR method, De-Novo multi-approaches multi-attributes analysis, failure mode and effect analysis (FMEA)
DOI: 10.3233/JIFS-162013
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 639-649, 2018
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