Finding minimum-cost flows by double scaling

Several researchers have recently developed new techniques that give fast algorithms for the minimum-cost flow problem. In this paper the authors combine several of these techniques to yield an algorithm running in O(nm(loglogU)log(nC)) time on networks with n vertices, m edges, maximum arc capacity U, and maximum arc cost magnitude C. The major techniques used are the capacity-scaling approach of Edmonds and Karp, the excess-scaling approach of Ahuja and Orlin, the cost-scaling approach of Goldberg and Tarjan, and the dynamic tree data structure of Sleator and Tarjan. For nonsparse graphs with large maximum arc capacity, the authors obtain a similar but slightly better bound. They also obtain a slightly better bound for the (noncapacitated) transportation problem. In addition, the authors discuss a capacity-bounding approach to the minimum-cost flow problem.