An approach to multiattribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights

This article proposes an approach to multiattribute decision making with incomplete attribute weight information where individual assessments are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). By employing a series of optimization models, the proposed approach derives a linear pr...

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Bibliographic Details
Published in:Information sciences 2009-08, Vol.179 (17), p.3026-3040
Main Authors: Wang, Zhoujing, Li, Kevin W., Wang, Weize
Format: Article
Language:English
Subjects:
Interval-valued intuitionistic fuzzy numbers (IVIFNs)
Linear programming
Multiattribute decision making
Uncertainty index
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Summary:This article proposes an approach to multiattribute decision making with incomplete attribute weight information where individual assessments are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). By employing a series of optimization models, the proposed approach derives a linear program for determining attribute weights. The weights are subsequently used to synthesize individual IVIFN assessments into an aggregated IVIFN value for each alternative. In order to rank alternatives based on their aggregated IVIFN values, a novel method is developed for comparing two IVIFNs by introducing two new functions: the membership uncertainty index and the hesitation uncertainty index. An illustrative investment decision problem is employed to demonstrate how to apply the proposed procedure and comparative studies are conducted to show its overall consistency with existing approaches.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2009.05.001