Approximation Algorithms For Network Flows
Approximation Algorithms for Network Flows is a computational methodology within algorithmic graph theory that belongs to the class of approximation algorithms and is specifically designed to efficiently compute near-optimal solutions for network flow problems where exact optimization is computationally intractable.
279
Publications
24K
Citations
493
Authors
249
Institutions
Publications per year
2017–2026
28
Parents
279
P-Complete Approximation Problems
Sartaj Sahni, Teofilo F. Gonzalez · Journal of the ACM · 1976 · 1.7K citations · Full text
Beyond the flow decomposition barrier
Andrew V. Goldberg, Satish Rao · Journal of the ACM · 1998 · 474 citations · Full text
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Princeton University
Princeton, United States
16 h-index
25 publications
9.6K citations
Massachusetts Institute of Technology
Cambridge, United States
14 h-index
23 publications
8.6K citations

Cornell University
Ithaca, United States
12 h-index
20 publications
2.6K citations
University of California, Berkeley
Berkeley, United States
10 h-index
14 publications
2.3K citations
Stanford University
Stanford, United States
10 h-index
15 publications
1.4K citations
Max Planck Society
Munich, Germany
8 h-index
11 publications
256 citations

Tel Aviv University
Tel Aviv, Israel
8 h-index
9 publications
342 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
7 h-index
10 publications
576 citations
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17 publications · 1.2K citations
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10 publications · 366 citations
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9 publications · 1.3K citations
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JACM · 8 publications · 3.6K citations
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6 publications · 281 citations
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