Fast algorithms for bipartite network flow
SIAM Journal on Computing
A new approach to the maximum-flow problem
Journal of the ACM (JACM)
A fast parametric maximum flow algorithm and applications
SIAM Journal on Computing
Improved time bounds for the maximum flow problem
SIAM Journal on Computing
Analysis of preflow push algorithms for maximum network flow
SIAM Journal on Computing
Finding minimum-cost circulations by successive approximation
Mathematics of Operations Research
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Improved Algorithms for Bipartite Network Flow
SIAM Journal on Computing
Augment or push: a computational study of bipartite matching and unit-capacity flow algorithms
Journal of Experimental Algorithmics (JEA)
Improvements in practical aspects of optimally scheduling web advertising
Proceedings of the 11th international conference on World Wide Web
SIAM Journal on Discrete Mathematics
Efficient preflow push algorithms
Computers and Operations Research
The Partial Augment---Relabel Algorithm for the Maximum Flow Problem
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
Contraction network for solving maximum flow problem
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
| Hi-index | 0.00 |
In this article, we present an experimental study of several maximum-flow algorithms in the context of unbalanced bipartite networks. Our experiments are motivated by a real-world problem of managing reservation-based inventory in Google content ad systems. We are interested in observing the performance of several push-relabel algorithms on our real-world datasets and also on some generated ones. Previous work suggested an important improvement for push-relabel algorithms on unbalanced bipartite networks: the two-edge push rule. We show how the two-edge push rule improves the running time. While no single algorithm dominates the results, we show there is one that has very robust performance in practice.