Document Type
Article
Publication Date
Fall 2011
Publication Title
Expert Systems with Applications
Volume
39
Issue
10
First Page
12462
Keywords
Multi-attribute decision making (MADM), Interval-valued intuitionistic fuzzy numbers (IVIFNs), Fractional programming, Quadratic programming
Last Page
13469
Abstract
This article proposes an approach to handle multi-attribute decision making (MADM) problems under the interval-valued intuitionistic fuzzy environment, in which both assessments of alternatives on attributes (hereafter, referred to as attribute values) and attribute weights are provided as interval-valued intuitionistic fuzzy numbers (IVIFNs). The notion of relative closeness is extended to interval values to accommodate IVIFN decision data, and fractional programming models are developed based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine a relative closeness interval where attribute weights are independently determined for each alternative. By employing a series of optimization models, a quadratic program is established for obtaining a unified attribute weight vector, whereby the individual IVIFN attribute values are aggregated into relative closeness intervals to the ideal solution for final ranking. An illustrative supplier selection problem is employed to demonstrate how to apply the proposed procedure.
DOI
10.1016/j.eswa.2011.04.027
Recommended Citation
Wang, Zhou-Jing; Li, Kevin W. Dr.; and Xu, Jianhui. (2011). A mathematical programming approach to multi-attribute decision making with interval-valued intuitionistic fuzzy assessment information. Expert Systems with Applications, 39 (10), 12462-13469.
https://scholar.uwindsor.ca/odettepub/59
Comments
NOTICE: this is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, 38, 10, (2012) http://dx.doi.org/10.1016/j.eswa.2011.04.027.”