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.
Highlights
Multiple criteria decision analysis (MCDA) problems are common
This paper presents the concept of the lower and upper inclusion comparison possibilities defined on interval-valued intuitionistic fuzzy sets (IVIFSs) and determines an interval-valued intuitionistic fuzzy inclusion comparison possibility
In the context of an IVIFS framework, this paper proposed an inclusion comparison-based method for solving multiple criteria decision-making problems under incomplete preference information
Summary
Multiple criteria decision analysis (MCDA) problems are common. Because uncertainty always exists, modeling uncertainty in subjective human management becomes increasingly important in decision analysis. Nayagam et al (2011) introduced a new accuracy function and proposed an MCDA method based on IVIFSs. Chen and Yang (2011) established optimization models to determine the criterion weights under incomplete information and developed group decision-making methods for IVIFS settings. Li (2011c) utilized the concept of inclusion comparison probabilities in his proposed closeness coefficient-based nonlinear programming method, his developed inclusion comparison probability is still defined upon IFSs, not IVIFSs. Considering the advantages of the inclusion comparison probability on IFSs, this paper extends the concept to propose an inclusion comparison possibility within the interval-valued intuitionistic fuzzy decision environment. The purpose of this paper is to develop a novel interval-valued intuitionistic fuzzy MCDA method by using inclusion comparison possibilities defined on IVIFSs. In a manner similar to TOPSIS, an inclusion-based index that considers positive and negative ideals is proposed.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
