A class of fuzzy random optimization: expected value models

2003 ◽  
Vol 155 (1-2) ◽  
pp. 89-102 ◽  
Author(s):  
Yian-Kui Liu ◽  
Baoding Liu
2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Chunquan Li ◽  
Jianhua Jin

Randomness and uncertainty always coexist in complex systems such as decision-making and risk evaluation systems in the real world. Intuitionistic fuzzy random variables, as a natural extension of fuzzy and random variables, may be a useful tool to characterize some high-uncertainty phenomena. This paper presents a scalar expected value operator of intuitionistic fuzzy random variables and then discusses some properties concerning the measurability of intuitionistic fuzzy random variables. In addition, a risk model based on intuitionistic fuzzy random individual claim amount in insurance companies is established, in which the claim number process is regarded as a Poisson process. The mean chance of the ultimate ruin is investigated in detail. In particular, the expressions of the mean chance of the ultimate ruin are presented in the cases of zero initial surplus and arbitrary initial surplus, respectively, if individual claim amount is an exponentially distributed intuitionistic fuzzy random variable. Finally, two illustrated examples are provided.


Author(s):  
YIAN-KUI LIU ◽  
JINWU GAO

This paper presents the independence of fuzzy variables as well as its applications in fuzzy random optimization. First, the independence of fuzzy variables is defined based on the concept of marginal possibility distribution function, and a discussion about the relationship between the independent fuzzy variables and the noninteractive (unrelated) fuzzy variables is included. Second, we discuss some properties of the independent fuzzy variables, and establish the necessary and sufficient conditions for the independent fuzzy variables. Third, we propose the independence of fuzzy events, and deal with its fundamental properties. Finally, we apply the properties of the independent fuzzy variables to a class of fuzzy random programming problems to study their convexity.


2008 ◽  
Vol 13 (2) ◽  
pp. 117-125 ◽  
Author(s):  
Yan-Kui Liu ◽  
Zhi-Qiang Liu ◽  
Jinwu Gao

Metrika ◽  
2004 ◽  
Vol 59 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Manuel Montenegro ◽  
Ana Colubi ◽  
Mar�a Rosa Casals ◽  
Mar�a �ngeles Gil

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