Minimum spanning tree problem of uncertain random network

2014 ◽  
Vol 28 (3) ◽  
pp. 565-574 ◽  
Author(s):  
Yuhong Sheng ◽  
Zhongfeng Qin ◽  
Gang Shi
Author(s):  
Yuhong Sheng ◽  
Gang Shi ◽  
Dan A. Ralescu

Entropy is a measure of the uncertainty associated with a variable whose value cannot be exactly predicted. Based on the notion of chance measure, a concept of uncertain random entropy is introduced and used to provide a quantitative measurement of the uncertainty associated with uncertain random variables and its properties are studied in this paper. Relative entropy is a measure of the difference between two distribution functions. In order to deal with the divergence of uncertain random variables via chance distributions, this paper proposes also the relative entropy for uncertain random variables, as well as it investigates some mathematical properties of this concept. As an application, a model is presented to formulate a minimum spanning tree problem with uncertain random edge weights involving a relative entropy chance distribution. Finally, a numerical example of an uncertain random network is put forward to illustrate the effectiveness of the proposed model.


1992 ◽  
Vol 23 (3) ◽  
pp. 1-12 ◽  
Author(s):  
Jungho Park ◽  
Ken'Ichi Hagihara ◽  
Nobuki Tokura ◽  
Toshimitsu Masuzawa

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