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We study the problem of computing the vitality of edges and vertices with respect to the $st$-max flow in undirected planar graphs, where the vitality of an edge/vertex is the $st$-max flow decrease when the edge/vertex is removed from the…

Data Structures and Algorithms · Computer Science 2023-05-05 Lorenzo Balzotti , Paolo G. Franciosa

We show that, for any graph optimization problem in which the feasible solutions can be expressed by a formula in monadic second-order logic describing sets of vertices or edges and in which the goal is to minimize the sum of the weights in…

Data Structures and Algorithms · Computer Science 2017-03-09 David Eppstein , Denis Kurz

We give an algorithm to route a multicommodity flow in a planar graph $G$ with congestion $O(\log k)$, where $k$ is the maximum number of terminals on the boundary of a face, when each demand edge lie on a face of $G$. We also show that our…

Discrete Mathematics · Computer Science 2010-08-24 Guyslain Naves , Christophe Weibel

The \emph{vitality} of an arc/node of a graph with respect to the maximum flow between two fixed nodes $s$ and $t$ is defined as the reduction of the maximum flow caused by the removal of that arc/node. In this paper we address the issue of…

Data Structures and Algorithms · Computer Science 2018-12-21 Giorgio Ausiello , Paolo Giulio Franciosa , Isabella Lari , Andrea Ribichini

We provide a new algebraic technique to solve the sequential flow problem in polynomial space. The task is to maximise the flow through a graph where edge capacities can be changed over time by choosing a sequence of capacity labelings from…

Optimization and Control · Mathematics 2026-02-09 Hugo Gimbert , Corto Mascle , Patrick Totzke

We pull together previously established graph-theoretical results to produce the algorithm in the paper's title. The glue are three easy elementary lemmas.

Data Structures and Algorithms · Computer Science 2018-07-12 Assaf Kfoury

We present a nearly-linear time algorithm for finding a minimum-cost flow in planar graphs with polynomially bounded integer costs and capacities. The previous fastest algorithm for this problem is based on interior point methods (IPMs) and…

Data Structures and Algorithms · Computer Science 2022-05-04 Sally Dong , Yu Gao , Gramoz Goranci , Yin Tat Lee , Richard Peng , Sushant Sachdeva , Guanghao Ye

In numerical linear algebra, considerable effort has been devoted to obtaining faster algorithms for linear systems whose underlying matrices exhibit structural properties. A prominent success story is the method of generalized nested…

Data Structures and Algorithms · Computer Science 2023-10-26 Sally Dong , Gramoz Goranci , Lawrence Li , Sushant Sachdeva , Guanghao Ye

We present a new strongly polynomial algorithm for generalized flow maximization that is significantly simpler and faster than the previous strongly polynomial algorithm [V\'egh16]. For the uncapacitated problem formulation, the complexity…

Data Structures and Algorithms · Computer Science 2020-02-14 Neil Olver , László A. Végh

Given in the plane a set $S$ of $n$ points and a set of disks centered at these points, the disk graph $G(S)$ induced by these disks has vertex set $S$ and an edge between two vertices if their disks intersect. Note that the disks may have…

Computational Geometry · Computer Science 2025-10-08 Bruce W. Brewer , Haitao Wang

We devise a constant-factor approximation algorithm for the maximization version of the edge-disjoint paths problem if the supply graph together with the demand edges form a planar graph. By planar duality this is equivalent to packing cuts…

Data Structures and Algorithms · Computer Science 2021-12-14 Chien-Chung Huang , Mathieu Mari , Claire Mathieu , Kevin Schewior , Jens Vygen

We present an algorithm that given a linear program with $n$ variables, $m$ constraints, and constraint matrix $A$, computes an $\epsilon$-approximate solution in $\tilde{O}(\sqrt{rank(A)}\log(1/\epsilon))$ iterations with high probability.…

Data Structures and Algorithms · Computer Science 2020-09-02 Yin Tat Lee , Aaron Sidford

It is known that a better than $2$-approximation algorithm for the girth in dense directed unweighted graphs needs $n^{3-o(1)}$ time unless one uses fast matrix multiplication. Meanwhile, the best known approximation factor for a…

Data Structures and Algorithms · Computer Science 2020-04-28 Mina Dalirrooyfard , Virginia Vassilevska Williams

The maximum capacity path problem is to find a path from a source to a sink which has the maximum capacity among all paths. This paper addresses an extension of this problem which considers loss factors. It is called the generalized maximum…

Discrete Mathematics · Computer Science 2023-12-12 Adrian Marius Deaconu , Javad Tayyebi , Mihai-Lucian Rîtan

In this paper, we present an improved algorithm for the maximum flow problem on general networks with $n$ vertices and $m$ arcs. We show how to solve the problem in $O(mn)$ time, when $m = O(n^{2-\epsilon})$, for some $0 <\epsilon \leq 1$.…

Data Structures and Algorithms · Computer Science 2013-10-30 Rahul Mehta

It is already known that in multicast (single source, multiple sinks) network, random linear network coding can achieve the maximum flow upper bound. In this paper, we investigate how random linear network coding behaves in general…

Information Theory · Computer Science 2012-10-09 Yuan Li

In this paper, we develop an $O((m \log k) {\rm MSF} (n,m,1))$-time algorithm to find a half-integral node-capacitated multiflow of the maximum total flow-value in a network with $n$ nodes, $m$ edges, and $k$ terminals, where ${\rm MSF}…

Data Structures and Algorithms · Computer Science 2018-10-30 Hiroshi Hirai

We provide faster strongly polynomial time algorithms solving maximum flow in structured $n$-node $m$-arc networks. Our results imply an $n^{\omega + o(1)}$-time strongly polynomial time algorithms for computing a maximum bipartite…

Data Structures and Algorithms · Computer Science 2025-10-24 Daniel Dadush , James B. Orlin , Aaron Sidford , László A. Végh

We develop an efficient parallel algorithm for answering shortest-path queries in planar graphs and implement it on a multi-node CPU/GPU clusters. The algorithm uses a divide-and-conquer approach for decomposing the input graph into small…

Data Structures and Algorithms · Computer Science 2015-03-26 Guillaume Chapuis , Hristo Djidjev

Let $G=(V,E)$ be a graph modelling a building or road network in which edges have-both travel times (lengths) and capacities associated with them. An edge's capacity is the number of people that can enter that edge in a unit of time. In…

Data Structures and Algorithms · Computer Science 2016-07-28 Di Chen , Mordecai Golin
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