Share:


An inclusion comparison approach for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets

    Ting-Yu Chen Affiliation

Abstract

The theory of interval-valued intuitionistic fuzzy sets provides an intuitive and feasible way of addressing uncertain and ambiguous properties. Many useful models and methods have been developed for multiple criteria decision analysis within the interval-valued intuitionistic fuzzy environment. In contrast to the elaborate existing methods, this paper establishes a simple and effective method for managing the sophisticated data expressed by interval-valued intuitionistic fuzzy sets. An inclusion comparison possibility defined on interval-valued intuitionistic fuzzy sets is proposed, and some important properties are investigated. Then, an inclusion-based index that considers positive and negative ideals is offered. Considering the maximal comprehensive inclusion-based indices, this paper constructs a linear programming model (for consistent information) and an integrated, nonlinear programming model (for inconsistent information) to estimate the criterion weights and the optimal ranking order of the alternatives under an incomplete preference structure. The feasibility of the proposed method is illustrated by a practical example of selecting a suitable bridge construction method, and a comparative analysis with other relevant methods is conducted to validate the effectiveness and applicability of the proposed methodology.


First published online: 02 Jun 2015

Keyword : interval-valued intuitionistic fuzzy set, multiple criteria decision analysis, inclusion comparison possibility, inclusion-based index, incomplete preference structure

How to Cite
Chen, T.-Y. (2016). An inclusion comparison approach for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets. Technological and Economic Development of Economy, 22(3), 357-392. https://doi.org/10.3846/20294913.2014.989930
Published in Issue
May 12, 2016
Abstract Views
86
PDF Downloads
70
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.