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All issues Volume 36 / No 5 (October 2018) JNWPU, 36 5 (2018) 955-962 References
Open Access
Issue
JNWPU
Volume 36, Number 5, October 2018
Page(s) 955 - 962
DOI https://doi.org/10.1051/jnwpu/20183650955
Published online 17 December 2018
  1. Goldberg A, Tarjan E. Efficient Maximum Flow Algorithms[J]. Communications of the ACM, 2014, 57(8): 82-89 [Article] [CrossRef] [Google Scholar]
  2. Liang C, Yu F R, Zhang X. Information-Centric Network Function Virtualization over 5g Mobile Wireless Networks[J]. IEEE Network, 2015, 29(3): 68-74 [Article] [CrossRef] [Google Scholar]
  3. Kosut O. Max-Flow Min-Cut for Power System Security Index Computation[C]//IEEE Sensor Array and Multichannel Signal Processing Workshop, 2015: 61-64 [Google Scholar]
  4. Chen Xiaoxu, Wu Heng, Wu Yuewen. Large-Scale Resource Scheduling Based on Minimum Cost Maximum Flow[J]. Journal of Software, 2017, 28(3): 598-610 (in Chinese) [Article] [Google Scholar]
  5. Ford L R, Fulkerson D R. Notes on Linear Programming, Part Ⅱ: Maximal Flow through a Network[M]. Santa Monica, RAND Corporation, 1977: 16-31 [Google Scholar]
  6. Karzanov A V. Determining the Maximal Flow in a Network by the Method of Preflows[J]. Doklady Mathematics, 1974, 15(1): 434-437 [Google Scholar]
  7. Schiopu C, Ciurea E. The Maximum Flows in Planar Dynamic Networks[J]. International Journal of Computers Communications & Control, 2016, 11(2): 282-291 [CrossRef] [Google Scholar]
  8. Goldberg AV, Hed S, Kaplan H, Tarjan RE, Werneck RF. Maximum Flows by Incremental Breadth-First Search[C]//European Symposium on Algorithms, 2011: 457-468 [Google Scholar]
  9. Ghaffari M, Karrenbauer A, Kuhn F. Near-Optimal Distributed Maximum Flow: Extended Abstract[C]//ACM Symposium on Principles of Distributed Computing, 2015: 81-90 [Google Scholar]
  10. Sherman J. Nearly Maximum Flows in Nearly Linear Time[C]//IEEE Symposium on Foundations of Computer Science, 2013: 263–– [Google Scholar]
  11. Liers F, Pardella G. Simplifying Maximum Flow Computations:The Effect of Shrinking and Good Initial Flows[J]. Discrete Applied Mathematics, 2011, 159(17): 2187-2203 [Article] [CrossRef] [Google Scholar]
  12. Dan G. Very Simple Methods for All Pairs Network Flow Analysis[J]. Siam Journal on Computing, 1990, 19(1): 143-155 [Article] [CrossRef] [Google Scholar]
  13. Zhang Y, Xu X, Hua B. Contracting Community for Computing Maximum Flow[C]//IEEE International Conference on Granular Computing, 2012: 651-656 [Google Scholar]
  14. Zhang Y P, Hua B, Jiang J, et al. Research on the Maximum Flow in Large-Scale Network[C]//International Conference on Computational Intelligence and Security(CIS), 2011: 482-486 [Google Scholar]
  15. Scheuermann B, Rosenhahn B. Slimcuts: Graphcuts for High Resolution Images Using Graph Reduction[C]//International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2011: 219-232 [Google Scholar]
  16. Zhen C, Zhang L. The Computation of Maximum Flow in Network Analysis Based on Quotient Space Theory[J]. Chinese Journal of Computers, 2015, 38(8): 1705-1712 [Article] [Google Scholar]
  17. Niklas B, Blelloch G, Shun J. Efficient Implementation of a Synchronous Parallel Push-Relabel Algorithm[C]//European Symposia on Algorithms, 2015: 106-117 [Google Scholar]
  18. Soner S, Ozturan C. Experiences with Parallel Multi-Threaded Network Maximum Flow Algorithm[J]. Partnership for Advanced Computing in Europe, 2013, 2013(1): 1-10 [Google Scholar]
  19. Benoit D, Dupont E, Zhang W. Distributed Max-Flow in Spark[EB/OL]. (2015-06-03)[2017-04-06]. <a href="http://stanford.edu/~rezab/classes/cme323/S15/projects/distributed_max_flow_report.pdf" target="_blank">http://stanford.edu/~rezab/classes/cme323/S15/projects/distributed_max_flow_report.pdf</a> [Google Scholar]
  20. Halim F, Yap R, Wu Y. A Mapreduce-Based Maximum-Flow Algorithm for Large Small-World Network Graphs[C]//International Conference on Distributed Computing Systems(ICDCS), 2011: 192-202 [Google Scholar]
  21. Goldfarb D, Grigoriadis M D. A Computational Comparison of the Dinic and Network Simplex Methods for Maximum Flow[J]. Annals of Operations Research, 1988, 13(1): 81-123 [Article] [CrossRef] [Google Scholar]
  22. Goldberg, A V. Two-Level Push-Relabel Algorithm for the Maximum Flow Problem[C]//The Fifth Conference on Algorithmic Aspects in Information Management, 2009: 212-225 [Google Scholar]

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