Efficient CUDA Algorithms for the Maximum Network Flow Problem

2012 ◽  
pp. 55-66
Author(s):  
Jiadong Wu ◽  
Zhengyu He ◽  
Bo Hong
Keyword(s):  
Network Flow ◽  
Flow Problem ◽  
Network Flow Problem ◽  
Maximum Network Flow

scholarly journals Maximum Network Flow Algorithms

2021 ◽  
Vol 6 ◽  
pp. 75-81
Author(s):  
Mohan Chandra Adhikari ◽  
Umila Pyakurel
Keyword(s):  
Network Flow ◽  
Flow Problem ◽  
Dynamic Networks ◽  
Maximum Flow ◽  
Incoming Flow ◽  
Network Flow Problem ◽  
Maximum Flow Problem ◽  
Augmenting Path ◽  
Families First ◽  
Maximum Network Flow

The aim of the maximum network flow problem is to push as much flow as possible between two special vertices, the source and the sink satisfying the capacity constraints. For the solution of the maximum flow problem, there exists a number of algorithms. The existing algorithms can be divided into two families. First, augmenting path algorithms that satisfy the conservation constraints at intermediate vertices and the second preflow push relabel algorithms that violates the conservation constraints at the intermediate vertices resulting incoming flow more than outgoing flow.In this paper, we study different algorithms that determine the maximum flow in the static and dynamic networks.

Bilevel Model for Adaptive Network Flow Problem

2018 ◽  
Vol 64 ◽  
pp. 105-114 ◽  
Author(s):  
Jean-François Baffier ◽  
Pierre-Louis Poirion ◽  
Vorapong Suppakitpaisarn
Keyword(s):  
Network Flow ◽  
Flow Problem ◽  
Adaptive Network ◽  
Network Flow Problem
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