Evaluation Of Infrastructure Projects By A Decision Model With Interval-Valued Intuitionistic Fuzzy Sets

Seyed Meysam Mousavi | S. Salimain | J. Antucheviciene

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=159400
Date :  2022/01/28
Publish in :    International Journal of Strategic Property Management


Keywords :infrastructure projects, multi-criteria decision-making (MCDM), interval-valued intuitionistic fuzzy sets (IVIFSs), relative preference alternative (RPR) method, multi-attributive border approximation area comparison (MABAC)و method, weighted aggregated sum product assessment (WASPAS) method

Abstract :

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Infrastructure projects (IPs) face numerous challenges to reach the predefined aims over their life-cycle. There are many difficulties in projects because of the variety of elements in project’s tendency and the dependency of the project on mainly national factors. Due to these difficulties and their practices, the projects meet with uncertainty. In this paper, an interval-valued intuitionistic fuzzy set (IVIFS) is used at identifying ambiguity in IPs. Also, a new multi-criteria decision-making (MCDM) model is presented to evaluate and select the suitable alternative in IPs. Hence, a new IVIF-relative preference alternative-multi-attributive border approximation area comparison (IVIF-RPR-MABAC), and IVIF-weighted aggregated sum product assessment (IVIF-WASPAS) are proposed in order to obtain the weights of decision makers (DMs) and criteria, and a new IVIF-RPR-MABAC method is proposed to rank the alternatives. In this paper, a combination of the three mentioned approaches creates proposed new hybrid model to evaluate the main factors and the projects. Furthermore, a real case study is applied from the literature to validate the efficiency and performance of the proposed model. Afterward, a comparative analysis is presented to validate the proposed approach by comparing the hybrid proposed model with two IVIF-TOPSIS and IVIF-extended-VIKOR methods. The final results confirm the efficiency of the proposed model in ranking the main alternatives of an MCDM problem. Moreover, the sensitivity analysis is reported to determine the affection of parameters on the final weighting and ranking outcomes.