A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation

Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends th...

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Main Authors: Tarifa Almulhim, Ludmil Mikhailov, Dong-Ling Xu
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2013-09-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
Online Access:http://www.ijimai.org/journal/sites/default/files/files/2013/06/ijimai20132_3_1_pdf_27045.pdf
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spelling doaj-e33d66ccad92474698416dfc5df1fba82020-11-25T00:59:20ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16602013-09-012371410.9781/ijimai.2013.231A Fuzzy Group Prioritization Method for Deriving Weights and its Software ImplementationTarifa AlmulhimLudmil MikhailovDong-Ling XuSeveral Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of multiple DMs . The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values, in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and does not require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to implement the proposed method for solving fuzzy group prioritization problems in MATLAB. Detailed numerical examples are used to illustrate the proposed approach.http://www.ijimai.org/journal/sites/default/files/files/2013/06/ijimai20132_3_1_pdf_27045.pdfDecision-levelFuzzyMethod
collection DOAJ
language English
format Article
sources DOAJ
author Tarifa Almulhim
Ludmil Mikhailov
Dong-Ling Xu
spellingShingle Tarifa Almulhim
Ludmil Mikhailov
Dong-Ling Xu
A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
International Journal of Interactive Multimedia and Artificial Intelligence
Decision-level
Fuzzy
Method
author_facet Tarifa Almulhim
Ludmil Mikhailov
Dong-Ling Xu
author_sort Tarifa Almulhim
title A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
title_short A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
title_full A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
title_fullStr A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
title_full_unstemmed A Fuzzy Group Prioritization Method for Deriving Weights and its Software Implementation
title_sort fuzzy group prioritization method for deriving weights and its software implementation
publisher Universidad Internacional de La Rioja (UNIR)
series International Journal of Interactive Multimedia and Artificial Intelligence
issn 1989-1660
publishDate 2013-09-01
description Several Multi-Criteria Decision Making (MCDM) methods involve pairwise comparisons to obtain the preferences of decision makers (DMs). This paper proposes a fuzzy group prioritization method for deriving group priorities/weights from fuzzy pairwise comparison matrices. The proposed method extends the Fuzzy Preferences Programming Method (FPP) by considering the different importance weights of multiple DMs . The elements of the group pairwise comparison matrices are presented as fuzzy numbers rather than exact numerical values, in order to model the uncertainty and imprecision in the DMs’ judgments. Unlike the known fuzzy prioritization techniques, the proposed method is able to derive crisp weights from incomplete and fuzzy set of comparison judgments and does not require additional aggregation procedures. A prototype of a decision tool is developed to assist DMs to implement the proposed method for solving fuzzy group prioritization problems in MATLAB. Detailed numerical examples are used to illustrate the proposed approach.
topic Decision-level
Fuzzy
Method
url http://www.ijimai.org/journal/sites/default/files/files/2013/06/ijimai20132_3_1_pdf_27045.pdf
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