Highly reliable stochastic flow network reliability estimation

2016 ◽  
Author(s):  
Hector Cancela ◽  
Leslie Murray ◽  
Gerardo Rubino
Keyword(s):  
Network Reliability ◽  
Reliability Estimation ◽  
Stochastic Flow ◽  
Flow Network

Modeling and Applications on Timed Stochastic-Flow Networks

2015 ◽  
Vol 22 (05) ◽  
pp. 1550023
Author(s):  
Shin-Guang Chen
Keyword(s):  
Network Reliability ◽  
Daily Life ◽  
Transportation Network ◽  
Stochastic Flow ◽  
Production Network ◽  
Flow Networks ◽  
Stochastic Behavior ◽  
Flow Network ◽  
Numerical Examples ◽  
Time Consumption

A stochastic-flow network (SFN) is a network whose flow has stochastic behavior or probabilistic multi-states. A timed stochastic-flow network (TSFN) is a SFN whose flow spends time to go through the network. Traditionally, the evaluation of network reliability does not consider time consumption for the flow to get through the network. However, there are lots of daily-life networks which can be regarded as TSFNs, such as the transportation network, the production network, etc. Their flow spends time to get through the network, and they are not yet explored in the literature. This paper proposes approaches to evaluate the reliability of such networks. Some numerical examples are discussed to illustrate the proposed method.

scholarly journals Efficient Estimation of Stochastic Flow Network Reliability

2019 ◽  
Vol 68 (3) ◽  
pp. 954-970 ◽  
Author(s):  
Hector Cancela ◽  
Leslie Murray ◽  
Gerardo Rubino
Keyword(s):  
Network Reliability ◽  
Efficient Estimation ◽  
Stochastic Flow ◽  
Flow Network

Static Network Reliability Estimation under the Marshall-Olkin Copula

2016 ◽  
Vol 26 (2) ◽  
pp. 1-28 ◽  
Author(s):  
Zdravko I. Botev ◽  
Pierre L'Ecuyer ◽  
Richard Simard ◽  
Bruno Tuffin
Keyword(s):  
Network Reliability ◽  
Reliability Estimation

A Comparative Study of Different Approaches for Finding the Upper Boundary Points in Stochastic-Flow Networks

2014 ◽  
Vol 10 (3) ◽  
pp. 13-23 ◽  
Author(s):  
Seyed Mehdi Mansourzadeh ◽  
Seyed Hadi Nasseri ◽  
Majid Forghani-elahabad ◽  
Ali Ebrahimnejad
Keyword(s):  
Information System ◽  
Comparative Study ◽  
Test Problems ◽  
Stochastic Flow ◽  
Flow Networks ◽  
Flow Network ◽  
Random Test ◽  
Boundary Points ◽  
Exclusion Method ◽  
Upper Boundary

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approaches such as inclusion-exclusion method, sum of disjoint products, etc. However, most of the algorithms have been compared via complexity results or through one or two benchmark networks. Thus, comparing those algorithms through random test problems can be desired. Here, the authors first state a simple improved algorithm. Then, by generating a number of random test problems and implementing the algorithms in MATLAB, the proposed algorithm is demonstrated to be more efficient than some existing ones in medium-sized networks. The performance profile introduced by Dolan and More is used for analyzing the output of programs.

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