L-fuzzy numbers and their properties
Information Sciences: an International Journal
Computers and Industrial Engineering
On Selecting an Algorithm for Fuzzy Optimization
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
Fuzzy hierarchical production planning (with a case study)
Fuzzy Sets and Systems
Enhanced Russell measure in fuzzy DEA
International Journal of Data Analysis Techniques and Strategies
First-order optimality conditions for fuzzy number quadratic programming with fuzzy coefficients
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
On the monotonicity of fuzzy-inference methods related to T-S inference method
IEEE Transactions on Fuzzy Systems - Special section on computing with words
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Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Information Sciences: an International Journal
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Fuzzy Sets and Systems
Fuzzy interval cooperative games
Fuzzy Sets and Systems
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Fuzzy Sets and Systems
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Fuzzy Sets and Systems
Computers and Electronics in Agriculture
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Advances in Fuzzy Systems
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Fuzzy Sets and Systems
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Fuzzy Sets and Systems
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The inequality relation between two fuzzy numbers is investigated. A certain type of such a relation motivated by practical interpretation is proposed, and its correspondence with the usual lattice-type relation generated by the extended maximum and minimum operators and its possible interpretation are discussed. The concept of R-L fuzzy number is introduced, the class of all R-L fuzzy numbers covering practically the whole set of normal convex fuzzy numbers. Comparing two R-L fuzzy numbers of the same type, the relation introduced in the paper may be replaced by four ordinary inequalities. This fact may be taken advantage of in optimization problems with linear fuzzy constraints.