Social choice axioms for fuzzy set aggregation
Fuzzy Sets and Systems - Special issue: Aggregation and best choices of imprecise opinions
Representation and application of fuzzy numbers
Fuzzy Sets and Systems - Special issue: fuzzy arithmetic
Using Yager's t-norms for aggregation of fuzzy intervals
Fuzzy Sets and Systems
Compensatory fuzzy multiple level decision making
Fuzzy Sets and Systems
ASA and its application to multi-criteria decision making (case study)
Fuzzy Sets and Systems
Reasonable properties for the ordering of fuzzy quantities (II)
Fuzzy Sets and Systems
Ranking fuzzy numbers using ω-weighted valuations
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
A context-dependent method for ordering fuzzy numbers using probabilites
Information Sciences—Informatics and Computer Science: An International Journal
A Constructive Numerical Method for the Comparison of Intervals
PPAM '01 Proceedings of the th International Conference on Parallel Processing and Applied Mathematics-Revised Papers
Paper: Rating and ranking of multiple-aspect alternatives using fuzzy sets
Automatica (Journal of IFAC)
Mathematics and Computers in Simulation
Towards efficient prediction of decisions under interval uncertainty
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
A new approach to the rule-base evidential reasoning: Stock trading expert system application
Expert Systems with Applications: An International Journal
An intelligent fuzzy agent for spatial reasoning in GIS
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
The operations on intuitionistic fuzzy values in the framework of Dempster-Shafer theory
Knowledge-Based Systems
An approach to generalization of fuzzy TOPSIS method
Information Sciences: an International Journal
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In real optimization we always meet two main groups of criteria: requirements of useful outcomes increasing or expenses decreasing and demands of lower uncertainty or, in other words, risk minimization. Therefore, it seems advisable to formulate optimization problem under conditions of uncertainty, at least, two-objective on the basis of local criteria of outcomes increasing or expenses reduction and risk minimization. Generally, risk may be treated as the uncertainty of obtained result. In the considered situation, the degree of risk (uncertainty) may be defined in a natural way through the width of final interval objective function at the point of optimum achieved. To solve the given problem, the two-objective interval comparison technique has been developed taking into account the probability of supremacy of one interval over the other one and relation of compared widths of intervals. To illustrate the efficiency of the proposed method, the simple examples of minimization of interval double-extreme discontinuous cost function and fuzzy extension of Rosenbrock's test function are presented.