An interval-valued intuitionistic fuzzy model based on extended VIKOR and MARCOS for sustainable supplier selection in organ transplantation networks for healthcare devices

Seyed Meysam Mousavi | J. Antucheviciene | S. Salimian

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=169787
Date :  2022/03/23
Publish in :    Sustainability


Keywords :supply chain management, sustainable organ transplantation networks, interval-valued intuitionistic fuzzy sets (IVIFSs), IVIF-similarity measure, IVIF-Shannon entropy approach, IVIF-E-VIKOR method, IVIF-MARCOS method

Abstract :

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The selection of proper healthcare device suppliers in sustainable organ transplantation networks has become an essential topic of increasing life expectancy. Assessment of sustainable healthcare device suppliers can be regarded as a complex multi-criteria decision-making (MCDM) problem that consists of multiple alternative solutions with sustainable criteria. For this reason, this paper proposes a new integrated MCDM model based on combining an extended vlsekriterijuska optimizacija i komoromisno resenje (E-VIKOR) and measurement alternatives and ranking according to the compromise solution (MARCOS) approaches under interval-valued intuitionistic fuzzy sets (IVIFSs). The aggregating technique of the E-VIKOR method is a strong point of this method compared to the original approach. The IVIFS is taken to cope with the uncertain situation of realworld applications. In this regard, an IVIF-similarity measure is introduced to compute weights of the decision-makers (DMs). The IVIF-Shannon entropy method is utilized to calculate the criteria weights, and a new hybrid proposed model is developed by presenting the IVIF-E-VIKOR method and IVIF-MARCOS, to calculate the ranking of sustainable supplier alternatives in organ transplantation networks to supply the surgery devices. Afterward, an illustrative example is introduced to evaluate the performance of the proposed model, and a comparative analysis is presented to confirm and validate the proposed approach. Moreover, sensitivity analysis for essential parameters of the proposed model is performed to assess their effects on outcomes.