Information Sciences: an International Journal
Applied multivariate statistical analysis
Applied multivariate statistical analysis
Group decision making and consensus under fuzzy preferences and fuzzy majority
Fuzzy Sets and Systems - Special issue dedicated to Professor Claude Ponsard
Extensions of the analytic hierarchy process in fuzzy environment
Fuzzy Sets and Systems
The Max-Min Delphi method and fuzzy Delphi method via fuzzy integration
Fuzzy Sets and Systems
Combination of fuzzy numbers representing expert opinions
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Direct approach processes in group decision making using linguistic OWA operators
Fuzzy Sets and Systems
A model of consensus in group decision making under linguistic assessments
Fuzzy Sets and Systems
Aggregation of fuzzy opinions under group decision making
Fuzzy Sets and Systems
On a class of fuzzy c-numbers clustering procedures for fuzzy data
Fuzzy Sets and Systems
A new approach for ranking fuzzy numbers by distance method
Fuzzy Sets and Systems
Fuzzy clustering procedures for conical fuzzy vector data
Fuzzy Sets and Systems
Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
A similarity-based bidirectional approximate reasoning method for decision-making systems
Fuzzy Sets and Systems
Multidimensional least-squares fitting with a fuzzy model
Fuzzy Sets and Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Comparison of fuzzy numbers using a fuzzy distance measure
Fuzzy Sets and Systems - Fuzzy intervals
Optimal consensus of fuzzy opinions under group decision making environment
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Optimisation and decision
On cluster-wise fuzzy regression analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Analysis and efficient implementation of a linguistic fuzzy c-means
IEEE Transactions on Fuzzy Systems
A theoretical development on a fuzzy distance measure for fuzzy numbers
Mathematical and Computer Modelling: An International Journal
Selecting the most preferable alternatives in a group decision making problem using DEA
Expert Systems with Applications: An International Journal
Aggregating preference ranking with fuzzy Data Envelopment Analysis
Knowledge-Based Systems
An agent-oriented decision support system combining fuzzy clustering and the AHP
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Fuzzy extension of TOPSIS model for group decision making under multiple criteria
Artificial Intelligence Review
A linguistic consensus model for Web 2.0 communities
Applied Soft Computing
REFSQ'13 Proceedings of the 19th international conference on Requirements Engineering: Foundation for Software Quality
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The objective of this paper is to automate a decision-aid tool, which provides homogeneous clusters from a set of heterogeneous opinions for a particular criterion to evaluate an item under group decision scheme. In such situation, decision-making by a group of experts becomes more realistic and consistent while they provide more or less homogeneous responses. But in real practice, the homogeneity among the opinions for a specific criterion to evaluate an item is not maintained due to the diversity among the experts' several cognitive factors as well as biasness. As a result, the group's overall effectiveness is suffered and making a true decision becomes difficult as well as sometimes confusing. In order to avoid the heterogeneity among the opinions (fuzzy numbers), we propose here a fuzzy clustering methodology based on a fuzzy distance measure. Also a ranking index is introduced on the basis of Ordered Weighted Average (OWA) operator. Finally, a fuzzy multi-criteria decision-making problem on a flight simulator software development project is considered here to employ the proposed technique. The results are discussed and compared.