Interval valued intuitionistic fuzzy sets
Fuzzy Sets and Systems
More on intuitionistic fuzzy sets
Fuzzy Sets and Systems
New operations defined over the intuitionistic fuzzy sets
Fuzzy Sets and Systems
Operators over interval valued intuitionistic fuzzy sets
Fuzzy Sets and Systems
Handling multicriteria fuzzy decision-making problems based on vague set theory
Fuzzy Sets and Systems
Vague sets are intuitionistic fuzzy sets
Fuzzy Sets and Systems
Fuzzy Optimization and Decision Making
Expert Systems with Applications: An International Journal
Fuzzy Optimization and Decision Making
Fuzzy Sets and Systems
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
Mathematical and Computer Modelling: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In this paper, we investigate the multiple attribute group decision making (MAGDM) problems, of which the attribute values in the group decision matrices provided by each decision maker (DM) is characterized by interval numbers. First, we define the concepts of attribute satisfactory interval and attribute dissatisfactory interval, respectively, according to each attribute values. Then we develop an approach for aggregating attribute satisfactory interval and attribute dissatisfactory interval into the collective attribute interval-valued intuitionistic fuzzy number (IVIFN), and then we obtain the collective interval-valued intuitionistic fuzzy decision matrix for group decision making. Next, we use the interval-valued intuitionistic fuzzy weighted averaging operator to aggregate all attribute values characterized by interval-valued intuitionistic fuzzy information to get the overall IVIFNs of alternatives. And then we use the score function and accuracy function to calculate the score and accuracy degree of each alternative value, and then rank the alternatives according to the score and accuracy degree of each alternative and select the most desirable one(s). And finally, we give an example for comprehensive pre-evaluation of air quality in Guangzhou, China during 16th Asian Olympic Games to illustrate in detail the decision process by the developed approach.