Network reliability maximization for stochastic-flow network subject to correlated failures using genetic algorithm and tabu search

2017 ◽  
Vol 50 (7) ◽  
pp. 1212-1231 ◽  
Author(s):  
Cheng-Ta Yeh ◽  
Yi-Kuei Lin ◽  
Jo-Yun Yang
Keyword(s):  
Genetic Algorithm ◽  
Tabu Search ◽  
Network Reliability ◽  
Stochastic Flow ◽  
Flow Network ◽  
Correlated Failures

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

scholarly journals A genetic algorithm to solve the robust design problem for a Flow Network with Node Failure

2020 ◽  
Vol 8 (4) ◽  
pp. 01-10
Author(s):  
Noha Hamdy ◽  
Moatamad Refaat Hassan ◽  
Mohamed Eid Hussein
Keyword(s):  
Genetic Algorithm ◽  
Robust Design ◽  
Design Problem ◽  
Network Reliability ◽  
Approximate Algorithm ◽  
Node Failure ◽  
Flow Network ◽  
Optimal Capacity ◽  
Optimal Node ◽  
Node Capacity

The robust design problem in a flow network is defined as search optimal node capacity that can be assigned such that the network still survived even under the node’s failure. This problem is considered as an NP-hard. So, this paper proposes a genetic algorithm-based approach to solve it for a flow network with node failure. The proposed based genetic approach is used to assign the optimal capacity for each node to minimize the total capacities and maximize the network reliability. The proposed approach takes the capacity for each critical node should have the maximum capacity (usually equals to the demand value) to alleviate that the reliability to drop to zero. Three network examples are used to show the efficiency of our algorithm. Also, the results obtained by our approach are compared with those obtained by the previous approximate algorithm.

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