The problem of linguistic approximation in clinical decision making
International Journal of Approximate Reasoning
Possibilistic linear programming for managing interest rate risk
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A framework for linguistic modelling
Artificial Intelligence
Fuzzy Optimization and Decision Making
Decider: A fuzzy multi-criteria group decision support system
Knowledge-Based Systems
Compensatory operators in fuzzy linear programming with multiple objectives
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
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In this paper, we propose a compensatory model for computing with words under discrete linguistic labels and incomplete weight information. This particular model will be useful in the context of multi-attribute decision making problems characterized by discrete linguistic attribute evaluations and partially-known weight information. This group of multi-attribute decision making problems may be modeled as multi-objective programs by using the concept of satisfactory degree, defined for each decision alternative under study. We derive a compensatory program which can be substituted for such multi-objective models. Further, we prove that the optimal solution of this compensatory program is a Pareto solution to the original multi-objective model. To show the working principles of this approach, we illustrate the procedure on two numerical examples from the published literature. We then analyze a concrete example we developed for illustrating the real-life meanings of several model constructs and managerial connotations of the results obtained by using this new approach.