General multiple-objective decision functions and linguistically quantified statements
International Journal of Man-Machine Studies - Lecture notes in computer science Vol. 174
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
A fuzzy constraint satisfaction problem in the wine industry
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Preference Approach to Fuzzy Linear Inequalities and Optimizations
Fuzzy Optimization and Decision Making
Solving Large-Scale Fuzzy and Possibilistic Optimization Problems
Fuzzy Optimization and Decision Making
Optimization of logistic systems using fuzzy weighted aggregation
Fuzzy Sets and Systems
Fuzzy multi-objective optimization for network design of integrated e-supply chains
International Journal of Computer Integrated Manufacturing
Fuzzy criteria for feature selection
Fuzzy Sets and Systems
Fault tolerant control using a fuzzy predictive approach
Expert Systems with Applications: An International Journal
Some concepts of the fuzzy multicommodity flow problem and their application in fuzzy network design
Mathematical and Computer Modelling: An International Journal
Expert Systems with Applications: An International Journal
Constrained optimization problems under uncertainty with coherent lower previsions
Fuzzy Sets and Systems
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Many practical optimization problems are characterized by some flexibility in the problem constraints, where this flexibility can be exploited for additional trade-off between improving the objective function and satisfying the constraints. Fuzzy sets have proven to be a suitable representation for modeling this type of soft constraints. Conventionally, the fuzzy optimization problem in such a setting is defined as the simultaneous satisfaction of the constraints and the goals. No additional distinction is assumed to exist amongst the constraints and the goals. This paper proposes an extension of this model for satisfying the problem constraints and the goals, where preference for different constraints and goals can be specified by the decision-maker. The difference in the preference for the constraints is represented by a set of associated weight factors, which influence the nature of trade-off between improving the optimization objectives and satisfying various constraints. Simultaneous weighted satisfaction of various criteria is modeled by using the recently proposed weighted extensions of (Archimedean) fuzzy t-norms. The weighted satisfaction of the problem constraints and goals are demonstrated by using a simple fuzzy linear programming problem. The framework, however, is more general, and it can also be applied to fuzzy mathematical programming problems and multi-objective fuzzy optimization.