A simpler and faster strongly polynomial algorithm for generalized flow maximization
A simpler and faster strongly polynomial algorithm for generalized flow maximization
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一种更简单、更快速的广义流最大化的强多项式算法
DOI:
10.1145/3055399.3055439
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发表时间:
2017
期刊:
影响因子:
--
通讯作者:
Olver N
中科院分区:
文献类型:
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作者:
Olver N
We present a new strongly polynomial algorithm for generalized flow maximization that is significantly simpler and faster than the previous strongly polynomial algorithm [34]. For the uncapacitated problem formulation, the complexity boundO(mn(m+nlogn)log (n2/m)) improves on the previous estimate by almost a factorO(n2). Even for small numerical parameter values, our running time bound is comparable to the best weakly polynomial algorithms. The key new technical idea is relaxing the primal feasibility conditions. This allows us to work almost exclusively with integral flows, in contrast to all previous algorithms for the problem.
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影响因子:
1.1
作者:
T. Radzik
通讯作者:
T. Radzik
DOI:
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发表时间:
2006
期刊:
ACM-SIAM Symposium on Discrete Algorithms
影响因子:
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作者:
Mateo Restrepo;David P. Williamson
通讯作者:
David P. Williamson
影响因子:
2.7
作者:
D. Goldfarb;Zhiying Jin;Yiqing Lin
通讯作者:
Yiqing Lin
DOI:
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发表时间:
1998
期刊:
Conference on Integer Programming and Combinatorial Optimization
影响因子:
--
作者:
É. Tardos;Kevin Wayne
通讯作者:
Kevin Wayne
DOI:
10.1287/moor.2013.0623
发表时间:
2011
期刊:
2012 IEEE 53rd Annual Symposium on Foundations of Computer Science
影响因子:
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作者:
László A. Végh
通讯作者:
László A. Végh