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Finding shortest paths in a given network (e.g., a computer network or a road network) is a well-studied task with many applications. We consider this task under the presence of an adversary, who can manipulate the network by perturbing its…

Social and Information Networks · Computer Science 2021-07-08 Benjamin A. Miller , Zohair Shafi , Wheeler Ruml , Yevgeniy Vorobeychik , Tina Eliassi-Rad , Scott Alfeld

Given a family $\mathcal{F}$ of graphs, a graph is \emph{$\mathcal{F}$-subgraph-free} if it has no subgraph isomorphic to a member of $\mathcal{F}$. We present a fixed-parameter linear-time algorithm that decides whether a planar graph can…

Discrete Mathematics · Computer Science 2025-10-20 Shinwoo An , Seonghyuk Im , Seokbeom Kim , Myounghwan Lee

In a series of papers, Avraham, Filtser, Kaplan, Katz, and Sharir (SoCG'14), Kaplan, Katz, Saban, and Sharir (ESA'23), and Katz, Saban, and Sharir (ESA'24) studied a class of geometric optimization problems -- including reverse shortest…

Data Structures and Algorithms · Computer Science 2025-04-10 Timothy M. Chan , Zhengcheng Huang

In undirected graphs with real non-negative weights, we give a new randomized algorithm for the single-source shortest path (SSSP) problem with running time $O(m\sqrt{\log n \cdot \log\log n})$ in the comparison-addition model. This is the…

Data Structures and Algorithms · Computer Science 2023-10-05 Ran Duan , Jiayi Mao , Xinkai Shu , Longhui Yin

Let $G=(V,E)$ be an $n$-nodes non-negatively real-weighted undirected graph. In this paper we show how to enrich a {\em single-source shortest-path tree} (SPT) of $G$ with a \emph{sparse} set of \emph{auxiliary} edges selected from $E$, in…

Data Structures and Algorithms · Computer Science 2015-07-08 Annalisa D'Andrea , Mattia D'Emidio , Daniele Frigioni , Stefano Leucci , Guido Proietti

We present two new and efficient algorithms for computing all-pairs shortest paths. The algorithms operate on directed graphs with real (possibly negative) weights. They make use of directed path consistency along a vertex ordering d. Both…

Data Structures and Algorithms · Computer Science 2014-01-21 Léon R. Planken , Mathijs M. de Weerdt , Roman P. J. van der Krogt

The paper presents fault-tolerant (FT) labeling schemes for general graphs, as well as, improved FT routing schemes. For a given $n$-vertex graph $G$ and a bound $f$ on the number of faults, an $f$-FT connectivity labeling scheme is a…

Data Structures and Algorithms · Computer Science 2021-06-02 Michal Dory , Merav Parter

Consider the following distance query for an $n$-node graph $G$ undergoing edge insertions and deletions: given two sets of nodes $I$ and $J$, return the distances between every pair of nodes in $I\times J$. This query is rather general and…

Data Structures and Algorithms · Computer Science 2019-10-18 Jan van den Brand , Danupon Nanongkai

Algebraic data structures are the main subroutine for maintaining distances in fully dynamic graphs in subquadratic time. However, these dynamic algebraic algorithms generally cannot maintain the shortest paths, especially against adaptive…

Data Structures and Algorithms · Computer Science 2023-11-28 Anastasiia Alokhina , Jan van den Brand

An important tool in the design of fault-tolerant graph data structures are $(L,f)$-replacement path coverings (RPCs). An RPC is a family $\mathcal{G}$ of subgraphs of a given graph $G$ such that, for every set $F$ of at most $f$ edges,…

Data Structures and Algorithms · Computer Science 2026-05-01 Davide Bilò , Shiri Chechik , Keerti Choudhary , Sarel Cohen , Martin Schirneck

The textbook algorithm for single-source shortest paths with real-valued edge weights runs in $O(m n)$ time on a graph with $m$ edges and $n$ vertices. A recent breakthrough algorithm by Fineman [Fin24] takes $\tilde O(m n^{8/9})$…

Data Structures and Algorithms · Computer Science 2024-12-10 Yufan Huang , Peter Jin , Kent Quanrud

A classical algorithm by Bellman and Ford from the 1950's computes shortest paths in weighted graphs on $n$ vertices and $m$ edges with possibly negative weights in $O(mn)$ time. Indeed, this algorithm is taught regularly in undergraduate…

Data Structures and Algorithms · Computer Science 2025-04-11 Satish Rao

We study computing {\em all-pairs shortest paths} (APSP) on distributed networks (the CONGEST model). The goal is for every node in the (weighted) network to know the distance from every other node using communication. The problem admits…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Chien-Chung Huang , Danupon Nanongkai , Thatchaphol Saranurak

Two-stage methods addressing continuous shortest path problems start local minimization from discrete shortest paths in a spatial graph. The convergence of such hybrid methods to global minimizers hinges on the discretization error induced…

Optimization and Control · Mathematics 2022-04-13 Ralf Borndörfer , Fabian Danecker , Martin Weiser

In a directed graph $G=(V,E)$ with a capacity on every edge, a \emph{bottleneck path} (or \emph{widest path}) between two vertices is a path maximizing the minimum capacity of edges in the path. For the single-source all-destination version…

Data Structures and Algorithms · Computer Science 2018-09-03 Ran Duan , Kaifeng Lyu , Hongxun Wu , Yuanhang Xie

We study {\em breadth-first search (BFS)} spanning trees, and address the problem of designing a sparse {\em fault-tolerant} BFS structure, or {\em FT-BFS } for short, resilient to the failure of up to two edges in the given undirected…

Data Structures and Algorithms · Computer Science 2015-05-05 Merav Parter

One of the classical line of work in graph algorithms has been the Replacement Path Problem: given a graph $G$, $s$ and $t$, find shortest paths from $s$ to $t$ avoiding each edge $e$ on the shortest path from $s$ to $t$. These paths are…

Data Structures and Algorithms · Computer Science 2020-05-22 Manoj Gupta , Rahul Jain , Nitiksha Modi

Let $G$ be an $n$-node simple directed planar graph with nonnegative edge weights. We study the fundamental problems of computing (1) a global cut of $G$ with minimum weight and (2) a~cycle of $G$ with minimum weight. The best previously…

Data Structures and Algorithms · Computer Science 2017-03-24 Hung-Chun Liang , Hsueh-I Lu

A straightforward dynamic programming method for the single-source shortest paths problem (SSSP) in an edge-weighted directed acyclic graph (DAG) processes the vertices in a topologically sorted order. First, we similarly iterate this…

Data Structures and Algorithms · Computer Science 2021-08-10 Andrzej Lingas , Mia Persson , Dzmitry Sledneu

In the decremental single-source shortest paths (SSSP) problem, the input is an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges undergoing edge deletions, together with a fixed source vertex $s\in V$. The goal is to maintain a…

Data Structures and Algorithms · Computer Science 2020-09-21 Julia Chuzhoy , Thatchaphol Saranurak
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