A fast cost scaling algorithm for submodular flow

Core Discussion Paper 9947 a Faster Capacity Scaling Algorithm for Minimum Cost Submodular Flow

We describe an O(nh min{log U, n log n}) capacity scaling algorithm for the minimum cost submodular flow problem. Our algorithm modifies and extends the Edmonds–Karp capacity scaling algorithm for minimum cost flow to solve the minimum cost submodular flow problem. The modification entails scaling a relaxation parameter δ. Capacities are relaxed by attaching a complete directed graph with unifo...

A Capacity Scaling Algorithm for M-convex Submodular Flow

This paper presents a faster algorithm for the M-convex submodular flow problem, which is a generalization of the minimum-cost flow problem with an M-convex cost function for the flow-boundary, where an M-convex function is a nonlinear nonseparable discrete convex function on integer points. The algorithm extends the capacity scaling approach for the submodular flow problem by Fleischer, Iwata ...

A faster capacity scaling algorithm for minimum cost submodular flow

We describe an O(nhmin{logU, n log n}) capacity scaling algorithm for the minimum cost submodular flow problem. Our algorithm modifies and extends the Edmonds–Karp capacity scaling algorithm for minimum cost flow to solve the minimum cost submodular flow problem. The modification entails scaling a relaxation parameter δ. Capacities are relaxed by attaching a complete directed graph with uniform...

A Strongly Polynomial Cut Canceling Algorithm for Minimum Cost Submodular Flow

This paper presents a new strongly polynomial cut canceling algorithm for minimum cost submodular flow. The algorithm is a generalization of our similar cut canceling algorithm for ordinary min-cost flow. The algorithm scales a relaxed optimality parameter, and creates a second, inner relaxation that is a kind of submodular max flow problem. The outer relaxation uses a novel technique for relax...

A Faster Capacity Scaling Algorithm for Minimum Cost Submodular Flow