Interval valued intuitionistic fuzzy sets
Fuzzy Sets and Systems
Group decision making procedure considering preference strength under incomplete information
Computers and Operations Research
Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Guest editorial: soft computing data mining
Information Sciences: an International Journal - Special issue: Soft computing data mining
Compromise ratio method for fuzzy multi-attribute group decision making
Applied Soft Computing
Generalizing TOPSIS for fuzzy multiple-criteria group decision-making
Computers & Mathematics with Applications
Group decision making based on multiple types of linguistic preference relations
Information Sciences: an International Journal
The interval-valued fuzzy TOPSIS method and experimental analysis
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Fuzzy Sets and Systems
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Expert Systems with Applications: An International Journal
A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods
Expert Systems with Applications: An International Journal
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
Group decision making problems in a linguistic and dynamic context
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
Intuitionistic Fuzzy Cognitive Maps for Medical Decision Making
IEEE Transactions on Information Technology in Biomedicine
Linguistic labels for expressing fuzzy preference relations infuzzy group decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An extension of TOPSIS for group decision making
Mathematical and Computer Modelling: An International Journal
Group decision making with multi-attribute interval data
Information Fusion
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In this paper, we investigate the group decision making problem, in which the each decision maker (DM) provides his/her preferences over alternatives with respect to attributes in interval-valued intuitionistic fuzzy number. To determine the weights of DMs, inspired by the idea of TOPSIS technique, combining an optimistic coefficient, we first define a positive ideal decision as the average of all individual decisions and three negative ideal decisions, which have the maximum separations from the positive ideal decision. This method is suitable for cautious (avoiding risk) decision, since each negative ideal decision can effectively avoid a risk. By employing the derived weights of DMs, we aggregate all the individual decisions into a collective decision. After that, we aggregate all attribute values of each alternative of the collective decision into an overall evaluation of the alternative. Then rank all alternatives according to their score and accuracy degree and select the most desirable one. We compare this model with other methods and illustrate this method by a numerical example and a sensitivity analysis about the optimistic coefficient.