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We consider the selective graph coloring problem, which is a generalization of the classical graph coloring problem. Given a graph together with a partition of its vertex set into clusters, we want to choose exactly one vertex per cluster…

Data Structures and Algorithms · Computer Science 2021-01-01 Oylum Şeker , Tınaz Ekim , Z. Caner Taşkın

The {\sc $c$-Balanced Separator} problem is a graph-partitioning problem in which given a graph $G$, one aims to find a cut of minimum size such that both the sides of the cut have at least $cn$ vertices. In this paper, we present new…

Data Structures and Algorithms · Computer Science 2010-11-22 Manjish Pal

The problems studied in this paper originate from Graph Motif, a problem introduced in 2006 in the context of biological networks. Informally speaking, it consists in deciding if a multiset of colors occurs in a connected subgraph of a…

Computational Complexity · Computer Science 2014-09-11 Romeo Rizzi , Florian Sikora

A dominating induced matching, also called an efficient edge domination, of a graph $G=(V,E)$ with $n=|V|$ vertices and $m=|E|$ edges is a subset $F \subseteq E$ of edges in the graph such that no two edges in $F$ share a common endpoint…

Data Structures and Algorithms · Computer Science 2017-08-08 Mingyu Xiao , Hiroshi Nagamochi

Recently a large number of graph separator problems have been proven to be \textsc{NP-Hard}. Amazingly we have found that $\alpha$-Subgraph-Balanced-Vertex-Separator, an important variant, has been overlooked. In this work ``Yet Another…

Computational Complexity · Computer Science 2014-03-24 Ryan H. Lewis

Let $G$ be a connected graph. The eccentricity of a path $P$, denoted by ecc$_G(P)$, is the maximum distance from $P$ to any vertex in $G$. In the \textsc{Central path} (CP) problem our aim is to find a path of minimum eccentricity. This…

Combinatorics · Mathematics 2022-02-08 Renzo Gómez , Juan Gutiérrez

Bi-level optimisation problems have gained increasing interest in the field of combinatorial optimisation in recent years. With this paper, we start the runtime analysis of evolutionary algorithms for bi-level optimisation problems. We…

Neural and Evolutionary Computing · Computer Science 2014-01-10 Dogan Corus , Per Kristian Lehre , Frank Neumann , Mojgan Pourhassan

Analyzing large graph data is an essential part of many modern applications, such as social networks. Due to its large computational complexity, distributed processing is frequently employed. This requires graph data to be divided across…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-12 YoungJoon Park , DongKyu Lee , Tien-Cuong Bui

Many exact search algorithms for NP-hard graph problems adopt the old Davis-Putman branch-and-reduce paradigm. The performance of these algorithms often suffers from the increasing number of graph modifications, such as vertex/edge…

Data Structures and Algorithms · Computer Science 2014-04-28 Faisal N. Abu-Khzam , Karim A. Jahed , Amer E. Mouawad

In this paper we present an algorithmic framework for solving a class of combinatorial optimization problems on graphs with bounded pathwidth. The problems are NP-hard in general, but solvable in linear time on this type of graphs. The…

Data Structures and Algorithms · Computer Science 2012-12-18 Mugurel Ionut Andreica

Balanced partitioning is often a crucial first step in solving large-scale graph optimization problems, e.g., in some cases, a big graph can be chopped into pieces that fit on one machine to be processed independently before stitching the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-10 Kevin Aydin , MohammadHossein Bateni , Vahab Mirrokni

Graph neural networks (GNNs) have achieved great success for a variety of tasks such as node classification, graph classification, and link prediction. However, the use of GNNs (and machine learning more generally) to solve combinatorial…

Machine Learning · Computer Science 2024-11-26 Frederik Wenkel , Semih Cantürk , Stefan Horoi , Michael Perlmutter , Guy Wolf

In recent years, graph neural networks (GNNs) have been widely applied in tackling combinatorial optimization problems. However, existing methods still suffer from limited accuracy when addressing that on complex graphs and exhibit poor…

Machine Learning · Computer Science 2025-11-13 Yuyao Long

We present a probabilistic graphical model formulation for the graph clustering problem. This enables to locally represent uncertainty of image partitions by approximate marginal distributions in a mathematically substantiated way, and to…

Computer Vision and Pattern Recognition · Computer Science 2016-01-12 Jörg Hendrik Kappes , Paul Swoboda , Bogdan Savchynskyy , Tamir Hazan , Christoph Schnörr

Many variations of the classical graph coloring model have been intensively studied due to their multiple applications; scheduling problems and aircraft assignments, for instance, motivate the robust coloring problem. This model gets to…

Discrete Mathematics · Computer Science 2023-05-17 Delia Garijo , Alberto Márquez , Rafael Robles

We consider the problem of partitioning the edges of a graph into as few paths as possible. This is a~subject of the classic conjecture of Gallai and a recurring topic in combinatorics. Regarding the complexity of partitioning a graph…

Data Structures and Algorithms · Computer Science 2026-02-16 Tomáš Masařík , Michał Włodarczyk , Mehmet Akif Yıldız

According to the structural balance theory, a signed graph is considered structurally balanced when it can be partitioned into a number of modules such that positive and negative edges are respectively located inside and between the…

Optimization and Control · Mathematics 2023-05-18 Nejat Arinik , Vincent Labatut , Rosa Figueiredo

The problem of extending partial geometric graph representations such as plane graphs has received considerable attention in recent years. In particular, given a graph $G$, a connected subgraph $H$ of $G$ and a drawing $\mathcal{H}$ of $H$,…

Computational Geometry · Computer Science 2020-07-13 Eduard Eiben , Robert Ganian , Thekla Hamm , Fabian Klute , Martin Nöllenburg

Hypergraph partitioning is a pervasive NP-hard problem, and accelerating its computation on GPU can both slice time-to-solution and raise quality of results. In this work, we implement a multi-level hypergraph partitioning algorithm on GPU…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-17 Marco Ronzani , Cristina Silvano

Evolutionary algorithms (EAs) are universal solvers inspired by principles of natural evolution. In many applications, EAs produce astonishingly good solutions. As they are able to deal with complex optimisation problems, they show great…

Neural and Evolutionary Computing · Computer Science 2024-09-25 Jakob Baumann , Ignaz Rutter , Dirk Sudholt
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