TY - GEN

T1 - A simpler and faster strongly polynomial algorithm for generalized flow maximization

AU - Olver, N.K.

AU - Végh, László

PY - 2017

Y1 - 2017

N2 - We present a new strongly polynomial algorithm for generalized flow maximization. The first strongly polynomial algorithm for this problem was given very recently by Végh; our new algorithm is much simpler, and much faster. The complexity bound O((m + nlogn)mnlog(n2/m)) improves on the previous estimate obtained by Végh by almost a factor O(n2). Even for small numerical parameter values, our algorithm is essentially as fast as the best weakly polynomial algorithms. The key new technical idea is relaxing primal feasibility conditions. This allows us to work almost exclusively with integral flows, in contrast to all previous algorithms for the problem.

AB - We present a new strongly polynomial algorithm for generalized flow maximization. The first strongly polynomial algorithm for this problem was given very recently by Végh; our new algorithm is much simpler, and much faster. The complexity bound O((m + nlogn)mnlog(n2/m)) improves on the previous estimate obtained by Végh by almost a factor O(n2). Even for small numerical parameter values, our algorithm is essentially as fast as the best weakly polynomial algorithms. The key new technical idea is relaxing primal feasibility conditions. This allows us to work almost exclusively with integral flows, in contrast to all previous algorithms for the problem.

KW - Generalized flow

KW - Network flow

KW - Strongly polynomial

UR - http://www.scopus.com/inward/record.url?scp=85024364692&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85024364692&partnerID=8YFLogxK

U2 - 10.1145/3055399.3055439

DO - 10.1145/3055399.3055439

M3 - Conference contribution

SP - 100

EP - 111

BT - Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing (STOC)

PB - ACM

ER -