Target Controllability in Multilayer Networks via Minimum-Cost Maximum-Flow Method

Author(s):  
Jie Ding ◽  
Changyun Wen ◽  
Guoqi Li ◽  
Pengfei Tu ◽  
Dongxu Ji ◽  
...  
Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1716
Author(s):  
Adrian Marius Deaconu ◽  
Delia Spridon

Algorithms for network flow problems, such as maximum flow, minimum cost flow, and multi-commodity flow problems, are continuously developed and improved, and so, random network generators become indispensable to simulate the functionality and to test the correctness and the execution speed of these algorithms. For this purpose, in this paper, the well-known Erdős–Rényi model is adapted to generate random flow (transportation) networks. The developed algorithm is fast and based on the natural property of the flow that can be decomposed into directed elementary s-t paths and cycles. So, the proposed algorithm can be used to quickly build a vast number of networks as well as large-scale networks especially designed for s-t flows.


Author(s):  
Rafael Aranguiz ◽  
Oscar Link ◽  
Jose Aliaga ◽  
Oscar Briones ◽  
Ruben Alarcon ◽  
...  

Estimation of the maximum scour depth is important for defining the size and depth of building foundations in order to avoid failure during a tsunami event (Jayaratne, et al 2016). Traditionally, tsunami scour has been studied in laboratory experiments that use solitary waves. However, it has been demonstrated that this type of wave does not represent well a real tsunami (Madsen et al, 2008). In addition, results from field surveys are based on the scour depth after the tsunami event, studying only the maximum flow depth, and ignoring other hydrodynamic features such as velocity and wave period, as well as sediment deposition. The main objective of this research is to estimate maximum tsunami scour around rectangular structures as a function of realistic tsunami variables.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/ykb-JyL7lsE


2003 ◽  
Vol 12 (01) ◽  
pp. 1-17
Author(s):  
Sungpack Hong ◽  
Taewhan Kim

Sub-micron feature sizes have resulted in a considerable portion of power to be dissipated on the buses, causing an increased attention on savings for power at the behavioral level and the RT level of design. This paper addresses the problem of minimizing power dissipated in the switching of the buses in the high-level synthesis of data-dominated behavioral descriptions. Unlike the previous approaches in which the minimization of the power consumed in buses has not been considered until operation scheduling is completed, our approach integrates the bus binding problem into scheduling to exploit the impact of scheduling on the reduction of power dissipated on the buses more fully and effectively. We accomplish this by formulating the problem into a flow problem in a network, and devising an efficient algorithm which iteratively finds the maximum flow of minimum cost solutions in the network. Experimental results on a number of benchmark problems show that given resource and global timing constraints our designs are 19.8% power-efficient over the designs produced by a random-move based solution, and 15.5% power-efficient over the designs by a clock-step based optimal solution.


2014 ◽  
Vol 25 (03) ◽  
pp. 307-329 ◽  
Author(s):  
YOSHIYUKI YAMAMOTO ◽  
KOUICHI HIRATA ◽  
TETSUJI KUBOYAMA

In this paper, we investigate the problem of computing structural sensitive variations of an unordered tree edit distance. First, we focus on the variations tractable by the algorithms including the submodule of a network algorithm, either the minimum cost maximum flow algorithm or the maximum weighted bipartite matching algorithm. Then, we show that both network algorithms are replaceable, and hence the time complexity of computing these variations can be reduced to O(nmd) time, where n is the number of nodes in a tree, m is the number of nodes in another tree and d is the minimum degree of given two trees. Next, we show that the problem of computing the bottom-up distance is MAX SNP-hard. Note that the well-known linear-time algorithm for the bottom-up distance designed by Valiente (2001) computes just a bottom-up indel (insertion-deletion) distance allowing no substitutions.


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