Data structures and network algorithms
Data structures and network algorithms
Self-adjusting binary search trees
Journal of the ACM (JACM)
A strongly polynomial minimum cost circulation algorithm
Combinatorica
Mathematical Programming: Series A and B
A new approach to the maximum flow problem
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
Solving minimum-cost flow problems by successive approximation
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
A data structure for dynamic trees
Journal of Computer and System Sciences
A faster strongly polynomial minimum cost flow algorithm
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
EFFICIENT GRAPH ALGORITHMS FOR SEQUENTIAL AND PARALLEL COMPUTERS
EFFICIENT GRAPH ALGORITHMS FOR SEQUENTIAL AND PARALLEL COMPUTERS
A faster strongly polynomial minimum cost flow algorithm
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Complementing missing and inaccurate profiling using a minimum cost circulation algorithm
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
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A classical algorithm for finding a minimum-cost circulation consists of repeatedly finding a residual cycle of negative cost and canceling it by pushing enough flow around the cycle to saturate an arc. We show that a judicious choice of cycles for canceling leads to a polynomial bound on the number of iterations in this algorithm. This gives a very simple strongly polynomial algorithm that uses no scaling. A variant of the algorithm that uses dynamic trees runs in O(nm(log n) min{log(nC), mlog n}) time on a network of n vertices, m arcs, and arc costs of maximum absolute value C. This bound is comparable to those of the fastest previously known algorithms.