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Related papers: Online Carpooling using Expander Decompositions

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Nearly three decades ago, Bar-Noy, Motwani and Naor showed that no online edge-coloring algorithm can edge color a graph optimally. Indeed, their work, titled "the greedy algorithm is optimal for on-line edge coloring", shows that the…

Data Structures and Algorithms · Computer Science 2021-05-17 Amin Saberi , David Wajc

Within the context of stochastic probing with commitment, we consider the online stochastic matching problem; that is, the one sided online bipartite matching problem where edges adjacent to an online node must be probed to determine if…

Data Structures and Algorithms · Computer Science 2021-01-07 Allan Borodin , Calum MacRury , Akash Rakheja

In the online bipartite matching problem with replacements, all the vertices on one side of the bipartition are given, and the vertices on the other side arrive one by one with all their incident edges. The goal is to maintain a maximum…

Data Structures and Algorithms · Computer Science 2018-05-07 Aaron Bernstein , Jacob Holm , Eva Rotenberg

Given an undirected graph G=(V,E), a collection (s_1,t_1),...,(s_k,t_k) of k source-sink pairs, and an integer c, the goal in the Edge Disjoint Paths with Congestion problem is to connect maximum possible number of the source-sink pairs by…

Data Structures and Algorithms · Computer Science 2011-07-14 Julia Chuzhoy

The ARRIVAL problem is to decide the fate of a train moving along the edges of a directed graph, according to a simple (deterministic) pseudorandom walk. The problem is in $NP \cap coNP$ but not known to be in $P$. The currently best…

Data Structures and Algorithms · Computer Science 2021-04-12 Bernd Gärtner , Sebastian Haslebacher , Hung P. Hoang

The bipartite matching problem in the online and streaming settings has received a lot of attention recently. The classical vertex arrival setting, for which the celebrated Karp, Vazirani and Vazirani (KVV) algorithm achieves a $1-1/e$…

Data Structures and Algorithms · Computer Science 2021-03-23 Michael Kapralov

We study a weighted online bipartite matching problem: $G(V_1, V_2, E)$ is a weighted bipartite graph where $V_1$ is known beforehand and the vertices of $V_2$ arrive online. The goal is to match vertices of $V_2$ as they arrive to vertices…

Data Structures and Algorithms · Computer Science 2014-09-09 Moses Charikar , Monika Henzinger , Huy L. Nguyen

Graph Crossing Number is a fundamental problem with various applications. In this problem, the goal is to draw an input graph $G$ in the plane so as to minimize the number of crossings between the images of its edges. Despite extensive…

Data Structures and Algorithms · Computer Science 2021-01-12 Julia Chuzhoy , Sepideh Mahabadi , Zihan Tan

We present the first polynomial-time algorithm for computing a near-optimal \emph{flow}-expander decomposition. Given a graph $G$ and a parameter $\phi$, our algorithm removes at most a $\phi\log^{1+o(1)}n$ fraction of edges so that every…

Data Structures and Algorithms · Computer Science 2026-04-29 Nikhil Bansal , Arun Jambulapati , Thatchaphol Saranurak

We present a new algorithm for approximating the number of triangles in a graph $G$ whose edges arrive as an arbitrary order stream. If $m$ is the number of edges in $G$, $T$ the number of triangles, $\Delta_E$ the maximum number of…

Data Structures and Algorithms · Computer Science 2021-07-16 Rajesh Jayaram , John Kallaugher

In the classic Dial-a-Ride Problem, a server travels in some metric space to serve requests for rides. Each request has a source, destination, and release time. We study a variation of this problem where each request also has a revenue that…

Data Structures and Algorithms · Computer Science 2013-10-29 Ananya Christman , William Forcier

We study the problem of computing an approximate maximum cardinality matching in the semi-streaming model when edges arrive in a \emph{random} order. In the semi-streaming model, the edges of the input graph G = (V,E) are given as a stream…

Data Structures and Algorithms · Computer Science 2020-05-04 Aaron Bernstein

We consider the following fundamental routing problem. An adversary inputs packets arbitrarily at sources, each packet with an arbitrary destination. Traffic is constrained by link capacities and buffer sizes, and packets may be dropped at…

Data Structures and Algorithms · Computer Science 2015-01-27 Guy Even , Moti Medina , Boaz Patt-Shamir

Ride-pooling is computationally challenging. The number of feasible rides grows with the number of travelers and the degree (capacity of the vehicle to perform a pooled ride) and quickly explodes to the sizes making the problem not solvable…

Data Structures and Algorithms · Computer Science 2022-08-05 Usman Akhtar , Rafal Kucharski

The dispersion problem has been widely studied in computational geometry and facility location, and is closely related to the packing problem. The goal is to locate n points (e.g., facilities or persons) in a k-dimensional polytope, so that…

Computational Geometry · Computer Science 2017-04-25 Jing Chen , Bo Li , Yingkai Li

The Maximum Carpool Matching problem is a star packing problem in directed graphs. Formally, given a directed graph $G = (V, A)$, a capacity function $ c: V \to N $, and a weight function $w : A \to R $, a feasible \emph{carpool matching}…

Discrete Mathematics · Computer Science 2016-12-06 Gilad Kutiel

In the Maximum Independent Set of Hyperrectangles problem, we are given a set of $n$ (possibly overlapping) $d$-dimensional axis-aligned hyperrectangles, and the goal is to find a subset of non-overlapping hyperrectangles of maximum…

Data Structures and Algorithms · Computer Science 2024-06-28 Mohit Garg , Debajyoti Kar , Arindam Khan

We study the problem of edge partitioning, where the goal is to partition the edge set of a graph into several parts. The replication factor of a vertex $v$ is the number of parts that contain edges incident to $v$. The goal is to minimize…

Discrete Mathematics · Computer Science 2026-05-08 Alexander Yakunin , Andrey Kupavskii , Alexander Sushin , Stanislav Moiseev

In the Upper Degree-Constrained Partial Orientation problem we are given an undirected graph $G=(V,E)$, together with two degree constraint functions $d^-,d^+ : V \to \mathbb{N}$. The goal is to orient as many edges as possible, in such a…

Data Structures and Algorithms · Computer Science 2014-10-13 Marek Cygan , Tomasz Kociumaka

An $(\epsilon,\phi)$-expander decomposition of a graph $G=(V,E)$ is a clustering of the vertices $V=V_{1}\cup\cdots\cup V_{x}$ such that (1) each cluster $V_{i}$ induces subgraph with conductance at least $\phi$, and (2) the number of…

Data Structures and Algorithms · Computer Science 2019-05-28 Yi-Jun Chang , Thatchaphol Saranurak