An eigenvector method for generating normalized interval and fuzzy weights
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Publication:856119
DOI10.1016/j.amc.2006.02.026zbMath1102.90359OpenAlexW2171764073MaRDI QIDQ856119
Ying-Ming Wang, Kwai Sang Chin
Publication date: 7 December 2006
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.amc.2006.02.026
analytic hierarchy processeigenvectormultiple criteria decision makingnormalizationfuzzy comparison matrixinterval comparison matrix
Management decision making, including multiple objectives (90B50) Theory of fuzzy sets, etc. (03E72)
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Cites Work
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- Interval priorities in AHP by interval regression analysis
- Fuzzy logarithmic least squares ranking method in analytic hierarchy process
- A fuzzy extension of Saaty's priority theory
- On the normalization of interval and fuzzy weights
- A goal programming method for obtaining interval weights from an interval comparison matrix
- Approximate articulation of preference and priority derivation
- Fuzzy hierarchical analysis
- Uncertainty and rank order in the analytic hierarchy process
- Multi-criteria decision analysis with fuzzy pairwise comparisons
- An action learning evaluation procedure for multiple criteria decision making problems
- Preference programming and inconsistent interval judgments
- A statistical approach to the analytic hierarchy process with interval judgements. I: Distributions on feasible regions
- Preference simulation and preference programming: Robustness issues in priority derivation
- Preference programming through approximate ratio comparisons
- Fuzzy least-squares priority method in the analytic hierarchy process
- On consistency and ranking of alternatives in fuzzy AHP
- Deriving priorities from fuzzy pairwise comparison judgements
- A fuzzy approach to deriving priorities from interval pairwise comparison judgements
- A probabilistic study of preference structures in the analytic hierarchy process with interval judgments
- A two-stage logarithmic goal programming method for generating weights from interval comparison matrices
- On lexicographic goal programming method for generating weights from inconsistent interval comparison matrices
- Analytic hierarchy process: an overview of applications
- Interval weight generation approaches based on consistency test and interval comparison matrices
- Multiobjective programming in optimization of the interval objective function
- Fuzzy hierarchical analysis revisited
- Fuzzy hierarchical analysis: The Lambda-Max method
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