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A new method for deriving priority weights by extracting consistent numerical-valued matrices from interval-valued fuzzy judgement matrix
journal contribution
posted on 2014-09-20, 00:00 authored by F Zhang, J Ignatius, Chee Peng LimChee Peng Lim, Y ZhaoIt is important to derive priority weights from interval-valued fuzzy preferences when a pairwise comparative mechanism is used. By focusing on the significance of consistency in the pairwise comparison matrix, two numerical-valued consistent comparison matrices are extracted from an interval fuzzy judgement matrix. Both consistent matrices are derived by solving the linear or nonlinear programming models with the aid of assessments from Decision Makers (DMs). An interval priority weight vector from the extracted consistent matrices is generated. In order to retain more information hidden in the intervals, a new probability-based method for comparison of the interval priority weights is introduced. An algorithm for deriving the final priority interval weights for both consistent and inconsistent interval matrices is proposed. The algorithm is also generalized to handle the pairwise comparison matrix with fuzzy numbers. The comparative results from the five examples reveal that the proposed method, as compared with eight existing methods, exhibits a smaller degree of uncertainty pertaining to the priority weights, and is also more reliable based on the similarity measure. © 2014 Elsevier Inc. All rights reserved.
History
Journal
Information SciencesVolume
279Pagination
280 - 300Publisher
ElsevierLocation
Philadelphia, United StatesPublisher DOI
ISSN
0020-0255Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, ElsevierUsage metrics
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No categories selectedKeywords
ConsistencyFuzzy judgment matrixPairwise comparison matrixPriority weight vectorScience & TechnologyTechnologyComputer Science, Information SystemsComputer ScienceANALYTIC HIERARCHY PROCESSPAIRWISE COMPARISON JUDGMENTSGOAL PROGRAMMING METHODGROUP DECISION-MAKINGPREFERENCE RELATIONSTRANSITIVITYMODELSAGGREGATIONISSUES
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