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A diversified AHP-tree approach for multiple-criteria supplier selection

A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern, in this study, a diversified AHP-tree approach was proposed. In the proposed diversified AHP-tree approach, the judgement matrix of a decis...

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Autor principal: Chen, Toly
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8052948/
http://dx.doi.org/10.1007/s10287-021-00397-6
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author Chen, Toly
author_facet Chen, Toly
author_sort Chen, Toly
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description A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern, in this study, a diversified AHP-tree approach was proposed. In the proposed diversified AHP-tree approach, the judgement matrix of a decision maker is decomposed into several subjudgement matrices, which are more consistent than the original judgement matrix and represent diverse viewpoints on the relative priorities of criteria. Thus, a nonlinear programming model was established and optimized, for which a genetic algorithm is designed. To assess the effectiveness of the proposed diversified AHP-tree approach, it was applied to a supplier selection problem. The experimental results showed that the application of the diversified AHP-tree approach enabled the selection of multiple diversified suppliers from a single judgement matrix. Furthermore, all suppliers selected using the diversified AHP-tree approach were somewhat ideal.
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spelling pubmed-80529482021-04-19 A diversified AHP-tree approach for multiple-criteria supplier selection Chen, Toly Comput Manag Sci Original Paper A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern, in this study, a diversified AHP-tree approach was proposed. In the proposed diversified AHP-tree approach, the judgement matrix of a decision maker is decomposed into several subjudgement matrices, which are more consistent than the original judgement matrix and represent diverse viewpoints on the relative priorities of criteria. Thus, a nonlinear programming model was established and optimized, for which a genetic algorithm is designed. To assess the effectiveness of the proposed diversified AHP-tree approach, it was applied to a supplier selection problem. The experimental results showed that the application of the diversified AHP-tree approach enabled the selection of multiple diversified suppliers from a single judgement matrix. Furthermore, all suppliers selected using the diversified AHP-tree approach were somewhat ideal. Springer Berlin Heidelberg 2021-04-17 2021 /pmc/articles/PMC8052948/ http://dx.doi.org/10.1007/s10287-021-00397-6 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Chen, Toly
A diversified AHP-tree approach for multiple-criteria supplier selection
title A diversified AHP-tree approach for multiple-criteria supplier selection
title_full A diversified AHP-tree approach for multiple-criteria supplier selection
title_fullStr A diversified AHP-tree approach for multiple-criteria supplier selection
title_full_unstemmed A diversified AHP-tree approach for multiple-criteria supplier selection
title_short A diversified AHP-tree approach for multiple-criteria supplier selection
title_sort diversified ahp-tree approach for multiple-criteria supplier selection
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8052948/
http://dx.doi.org/10.1007/s10287-021-00397-6
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