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A hybrid decision support model using Grey Relational Analysis and the Additive-Veto Model for solving multicriteria decision-making problems: an approach to supplier selection

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Abstract

This paper puts forward a new hybrid Grey Additive-Veto Model (GAVM) for selecting suppliers, which optimizes the choice by the decision-maker’s (DM) preference. This study uses a Multi-Criteria Decision Making (MCDM) approach. The model proposed incorporates the uncertainty of real-world decision problems, through the Grey Numbers. Given the DM’s compensatory rationality, the method reflects tradeoffs amongst different criteria. However, a compensatory model may not represent the DM faithfully and realistically. For this is proposed a performance veto condition. Additionally, the DM may consider that suppliers with a high uncertainty are not desirable or even that they are not acceptable. For this is also proposed width performance veto condition. Given practical implications, the need for an enriched analysis of the ranking is perceived because during the ranking process, there are some situations in which the DM is undecided (mistrust, hesitation) about the statement that a given supplier is better ranked than another supplier. This hesitation is mainly caused by uncertainty arising from the grey numbers, and from attitudes, functions and characteristics of vetoes that the DM has defined. As findings, this paper shows that GAVM is suited to dealing with multicriteria decisions with uncertain information, veto conditions and its potential applicability is illustrated by a numerical supplier selection example. In addition, the numerical example shows that the enriched analysis of the ranking proposed can be conducted to direct the DM’s efforts to further enriching the insights for more assertive and coherent decision-making.

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Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES) (Finance Code 001), by the Brazilian National Research Council (CNPq), and by the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE) (Finance Code IBPG-1295-3.08/16).

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Correspondence to Thalles Vitelli Garcez.

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Garcez, T.V., Cavalcanti, H.T. & de Almeida, A.T. A hybrid decision support model using Grey Relational Analysis and the Additive-Veto Model for solving multicriteria decision-making problems: an approach to supplier selection. Ann Oper Res 304, 199–231 (2021). https://doi.org/10.1007/s10479-021-04103-2

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  • DOI: https://doi.org/10.1007/s10479-021-04103-2

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