On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Triangular norm-based iterative compensatory operators
Fuzzy Sets and Systems - Special issue on triangular norms
On the use of Hamacher's t-norms family for information aggregation
Information Sciences: an International Journal
Journal of the American Society for Information Science and Technology
Information Sciences: an International Journal
Prioritized aggregation operators
International Journal of Approximate Reasoning
A generalized model for prioritized multicriteria decision making systems
Expert Systems with Applications: An International Journal
Fuzzy Optimization and Decision Making
On prioritized weighted aggregation in multi-criteria decision making
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Full reinforcement operators in aggregation techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling prioritized multicriteria decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Parametric classes of generalized conjunction and disjunction operations for fuzzy modeling
IEEE Transactions on Fuzzy Systems
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There may exist priority relationships among criteria in multi-criteria decision making (MCDM) problems. This kind of problems, which we focus on in this paper, are called prioritized MCDM ones. In order to aggregate the evaluation values of criteria for an alternative, we first develop some weighted prioritized aggregation operators based on triangular norms (t-norms) together with the weights of criteria by extending the prioritized aggregation operators proposed by Yager (Yager, R. R. (2004). Modeling prioritized multi-criteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, 34, 2396-2404). After discussing the influence of the concentration degrees of the evaluation values with respect to each criterion to the priority relationships, we further develop a method for handling the prioritized MCDM problems. Through a simple example, we validate that this method can be used in more wide situations than the existing prioritized MCDM methods. At length, the relationships between the weights associated with criteria and the preference relations among alternatives are explored, and then two quadratic programming models for determining weights based on multiplicative and fuzzy preference relations are developed.