Abstract
The aim of this paper is to develop useful likelihood-based assignment methods for addressing multiple criteria decision-making problems within the environment of interval-valued intuitionistic fuzzy sets. Based on the likelihoods of interval-valued intuitionistic fuzzy preference relations, this paper determines the mean likelihoods of outranking relations and presents a mean likelihood determination method for generating a set of criterion-wise rankings of alternatives. By employing the concepts of rank frequency matrices and (ordinary) rank contribution matrices, this paper establishes a likelihood-based linear assignment model for multiple criteria decision analysis in the interval-valued intuitionistic fuzzy context. Additionally, this paper propounds two likelihood-based assignment models for handling incomplete and conflicting certain information of importance weights. These models can transform the criterion-wise ranks into the overall ranks for determining the optimal priority ranking of the alternatives. The feasibility and applicability of the proposed methods are illustrated with a practical problem of selecting a bridge construction method which involves various preference types. Finally, this paper conducts a comparative analysis with previous assignment-based methods in an interval-valued intuitionistic fuzzy setting to validate the effectiveness and advantages of the proposed methods.
Original language | English |
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Pages (from-to) | 425-457 |
Number of pages | 33 |
Journal | Fuzzy Optimization and Decision Making |
Volume | 14 |
Issue number | 4 |
DOIs | |
State | Published - 01 12 2015 |
Bibliographical note
Publisher Copyright:© 2015, Springer Science+Business Media New York.
Keywords
- Comparative analysis
- Interval-valued intuitionistic fuzzy set
- Likelihood-based assignment method
- Mean likelihood determination method
- Multiple criteria decision analysis