An Optimized Cost Flow Algorithm to Spread Cells in Detailed Placement

2019 ◽  
Vol 24 (3) ◽  
pp. 1-16
Author(s):  
Jucemar Monteiro ◽  
Marcelo Johann ◽  
Laleh Behjat
Keyword(s):  
Flow Algorithm ◽  
Cost Flow ◽  
Detailed Placement

scholarly journals Optimization of memory use of fragment extension-based protein–ligand docking with an original fast minimum cost flow algorithm

2018 ◽  
Vol 74 ◽  
pp. 399-406
Author(s):  
Keisuke Yanagisawa ◽  
Shunta Komine ◽  
Rikuto Kubota ◽  
Masahito Ohue ◽  
Yutaka Akiyama
Keyword(s):  
Minimum Cost ◽  
Ligand Docking ◽  
Minimum Cost Flow ◽  
Flow Algorithm ◽  
Cost Flow

Improved Minimum Cost Flow Algorithm for Phase Unwrapping

2021 ◽  
Vol 41 (2) ◽  
pp. 0210001
Author(s):  
邵珩 Shao Heng ◽  
周勇 Zhou Yong ◽  
聂中原 Nie Zhongyuan ◽  
祁俊峰 Qi Junfeng
Keyword(s):  
Minimum Cost ◽  
Phase Unwrapping ◽  
Minimum Cost Flow ◽  
Flow Algorithm ◽  
Cost Flow

scholarly journals Optimizing the minimum cost flow algorithm for the phase unwrapping process in SAR radar

2014 ◽  
Vol 62 (3) ◽  
pp. 511-516 ◽  
Author(s):  
J. Dudczyk ◽  
A. Kawalec
Keyword(s):  
Minimum Cost ◽  
Phase Unwrapping ◽  
Minimum Cost Flow ◽  
Field Methods ◽  
Phase Gradient ◽  
Partial Derivatives ◽  
Flow Algorithm ◽  
Cost Flow ◽  
Derivatives Of ◽  
Branch Cuts

Abstract The last three decades have been abundant in various solutions to the problem of Phase Unwrapping in a SAR radar. Basically, all the existing techniques of Phase Unwrapping are based on the assumption that it is possible to determine discrete ”derivatives” of the unwrapped phase. In this case a discrete derivative of the unwrapped phase means a phase difference (phase gradient) between the adjacent pixels if the absolute value of this difference is less than π. The unwrapped phase can be reconstructed from these discrete derivatives by adding a constant multiple of 2π. These methods differ in that the above hypothesis may be false in some image points. Therefore, discrete derivatives determining the unwrapped phase will be discontinuous, which means they will not form an irrotational vector field. Methods utilising branch-cuts unwrap the phase by summing up specific discrete partial derivatives of the unwrapped phase along a path. Such an approach enables internally cohesive results to be obtained. Possible summing paths are limited by branch-cuts, which must not be intersected. These branch-cuts connect local discontinuities of discrete partial derivatives. The authors of this paper performed parametrization of the Minimum Cost Flow algorithm by changing the parameter determining the size of a tile, into which the input image is divided, and changing the extent of overlapping of two adjacent tiles. It was the basis for determining the optimum (in terms of minimum Phase Unwrapping time) performance of the Minimum Cost Flow algorithm in the aspect of those parameters.

scholarly journals An O (n 2 (m + N log n )log n ) min-cost flow algorithm

1988 ◽  
Vol 35 (2) ◽  
pp. 374-386 ◽  
Author(s):  
Zvi Galil ◽  
Éva Tardos
Keyword(s):  
Flow Algorithm ◽  
Cost Flow ◽  
Min Cost Flow
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