1998/12/08 by David R. Karger, Karger, David R. · 13 citations
Computer Science · Engineering · #Computational Geometry and Mesh Generation #Data Structures and Algorithms (cs.DS) #F.2.2 #FOS: Computer and information sciences #G.2.2 #G.3 #Manufacturing Process and Optimization #Optimization and Packing Problems #cs.DS
paper · pdf · doi:10.48550/arxiv.cs/9812007
arxiv created 1998/12/08 · openalex publication_date 1998/12/08 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We significantly improve known time bounds for solving the minimum cut problem on undirected graphs. We use a ``semi-duality'' between minimum cuts and maximum spanning tree packings combined with our previously developed random sampling techniques. We give a randomized algorithm that finds a minimum cut in an m-edge, n-vertex graph with high probability in O(m log3 n) time. We also give a simpler randomized algorithm that finds all minimum cuts with high probability in O(n2 log n) time. This variant has an optimal RNC parallelization. Both variants improve on the previous best time bound of O(n2 log3 n). Other applications of the tree-packing approach are new, nearly tight bounds on the number of near minimum cuts a graph may have and a new data structure for representing them in a space-efficient manner.