Measurability criteria for fuzzy random vectors
Fuzzy Optimization and Decision Making
Risk management in uncapacitated facility location models with random demands
Computers and Operations Research
The modes of convergence in the approximation of fuzzy random optimization problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on Uncertainty Analysis and Decision Making; Guest Editors: Yan-Kui Liu, Baoding Liu, Jinwu Gao
Fuzzy random renewal process with queueing applications
Computers & Mathematics with Applications
Uncertainty Theory
Portfolio optimization problems in different risk measures using genetic algorithm
Expert Systems with Applications: An International Journal
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
The Approximation Method for Two-Stage Fuzzy Random Programming With Recourse
IEEE Transactions on Fuzzy Systems
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In a stochastic decision system, mean-risk is an approach frequently used for modeling the choice among random outcomes, the method quantifies a risk management problem by two criteria (i.e., mean and risk) with possible trade-off analysis In the literature, there are different risk definitions for a random variable such as variance, critical probability and stochastic dominance This paper presents semivariance of fuzzy random variable as a new risk criteria for measuring hybrid uncertain outcomes Since the semivariance is defined by nonlinear fuzzy integral, its computation is a challenge issue for research, and usually depends on intelligent algorithms This paper will develop some useful semivariance formulas for common triangular and trapezoidal fuzzy random variables, which have potential applications in various practical risk management problems.