A polynomial combinatorial algorithm for generalized minimum cost flow
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A Strongly Polynomial Cut Canceling Algorithm for the Submodular Flow Problem
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This paper presents two new scaling algorithms for the minimum cost network flow problem, one a primal cycle canceling algorithm, the other a dual cut canceling algorithm. Both algorithms scale a relaxed optimality parameter, and create a second, inner relaxation. The primal algorithm uses the inner relaxation to cancel a most negative node-disjoint family of cycles w.r.t. the scaled parameter, the dual algorithm uses it to cancel most positive cuts w.r.t. the scaled parameter. We show that in a network withn nodes andm arcs, both algorithms need to cancel onlyO(mn) objects per scaling phase.Furthermore, we show how to efficiently implement both algorithms to yield weakly polynomial running times that are as fast as any other cycle or cut canceling algorithms. Our algorithms have potential practical advantages compared to some other canceling algorithms as well.Along the way, we give a comprehensive survey of cycle and cut canceling algorithms for min-cost flow. We also clarify the formal duality between cycles and cuts.