.png){kind=icon}
.png){kind=icon}
Return
Uncertain random shortest path problem
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-018-03714-5.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The shortest path is an important problem in network optimization theory. This paper considers the shortest path problem under the situation where weights of edges in a network include both uncertainty and randomness and focuses on the case that the weights of edges are expressed by uncertain random variables. Some optimization models based on chance theory are proposed in order to find the shortest path which fully reflects uncertain and random information. This paper proposes also an intelligent algorithm to calculate the shortest path for an uncertain random network. A numerical example is given to illustrate its effectiveness.
Keywords:
Shortest path problem
Chance theory
Uncertain random variable
Uncertain random network
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.