Evaluating and Designing the Quality of Web Sites
IEEE MultiMedia
Fuzzy Sets and Systems - Optimisation and decision
A new fuzzy operator and its application to topology design of distributed local area networks
Information Sciences: an International Journal
Fuzzy preference relations: Aggregation and weight determination
Computers and Industrial Engineering
A Fuzzy Decision Support System for Garment New Product Development
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
A linguistic intelligent user guide for method selection in multi-objective decision support systems
Information Sciences: an International Journal
A linguistic multi-criteria group decision support system for fabric hand evaluation
Fuzzy Optimization and Decision Making
A general class of simple majority decision rules based on linguistic opinions
Information Sciences: an International Journal
The orness measures for two compound quasi-arithmetic mean aggregation operators
International Journal of Approximate Reasoning
Group decision making with triangular fuzzy linguistic variables
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Standard and mean deviation methods for linguistic group decision making and their applications
Expert Systems with Applications: An International Journal
A systematic approach to heterogeneous multiattribute group decision making
Computers and Industrial Engineering
Adaptive consensus support model for group decision making systems
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
| Hi-index | 0.00 |
This paper proposes improvements to pairwise group decision making based on fuzzy preference relations in three ways. First, it extends the fuzzy preference relation representation using linguistic labels. Decision makers may express their preference relations in linguistic labels which are more practically implementable for solving group decision making problems. Second, it modifies the computational procedures by using fuzzy sets representation and computation, and by avoiding the use of strict threshold values. This allows natural representation, preserves the preference accuracy, and produces more intuitively meaningful solutions. Finally, it considers fuzzy criteria of the alternatives explicitly. Solutions are first derived based on each criterion, and then by using neat ordered weighted average (OWA) operator the final solutions which accommodate all criteria are determined. The proposed method is verified for solving fuzzy group decision making problems, i.e., advertising media selection cases